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LSAC Data User Guide 2103 - Growing Up in Australia: The

1. Waves2 amp 3 or Waves 1 2 amp 3 bcwtd B Day 1 2 amp 3 Longitudinal analyses involving T Waves2 amp 3 or Waves 1 2 amp 3 dweight Population 1 amp 4 Wave 4 cross sectional analyses and longitudinal analyses ree ee ee involving Waves 1 amp 4 dweights B Sample 1 amp 4 Wave 4 cross sectional analyses and longitudinal analyses eae E eee involving Waves 1 amp 4 eweight Population 1 amp 5 Wave 5 cross sectional analyses and longitudinal analyses RIS involving Waves amp 5 eweights B Sample 1 amp 5 Wave 5 cross sectional analyses and longitudinal analyses N involving Waves amp 5 bdwt B Population 1 244 Longitudinal analyses involving Locum eec cogn cL e Dee LU Waves 2 amp 4 or Waves 1 2 amp 4 bdwts B Sample 12 amp 4 Longitudinal analyses involving T tee Se pes Waves 2 amp 4 or Waves 1 2 amp 4 cdwt B Population 1 344 Longitudinal analyses involving ee Waves 3 amp 4 or Waves 1 3 amp 4 cdwts B Sample 13 amp 4 Longitudinal analyses involving Waves 3 amp 4 or Waves 1 3 amp 4 bcdwt B Population 1 2 3 amp 4 Longitudinal analyses involving Waves 2 3 amp 4 or Waves 1 2 384 bcdwts Sample 1 2 3 amp 4 Longitudinal analyses involving Waves 2 3 amp 4 or Waves 1 2 a ase eae 364 bcdewt Population 1 2 3 4 Longitudinal analyses involving amp 5 Waves 2 3 4
2. lt stratumfile gt is a file that contains the number of Primary Sampling Units in this case postcode clusters in each stratum It is included on the data CD or can be set up using the following code data stratum input stratum _total_ datalines 11 295 13 168 14 160 21 202 22 58 23 95 24 316 31116 33 121 34 108 41 110 43 34 44 131 51 82 52 86 53 32 54 103 61 28 63 38 719 733 741 81 23 run LSAC Data User Guide November 2013 70 13 2 Unit of analysis The child is the unit of selection in LSAC and estimates produced from this survey are of children not of parents or families It is important this point is understood when producing population estimates from this survey Using the estimates to count families parents will produce an over count of the number of families parents due to the multiple or over counting of children from multiple births Although this will not make a huge difference to the actual numbers it may be important in the interpretation of the information and in comparing data from other sources Although it is possible to produce family weights it is not considered a worthwhile use of resources given the small number of analyses this could possibly meaningfully affect 13 3 Age at interview Different ages of children should be accounted for in any analyses focused on age dependent measures such as cognitive and motor development Figures 8 and 9 show the age distributio
3. The Who am I is a direct child assessment measure that requires children to copy shapes circle triangle cross square and diamond and write numbers letters words and sentences For the LSAC testing there was a change to Who Am I Item 11 This is a picture of me was replaced with a sentence to be copied John is big The Who am I assessment was used for the children at ages 4 5 years Wave 1 K and Wave 3 B cohorts to assess the general cognitive abilities needed for beginning school The study child was given his her own answer booklet to draw and write in What they wrote drew was assessed by experienced researchers at Australian Council for Educational Research ACER See the new Data Issues series for details of the Rasch Modelling used to score the WAI 5 1 3 Peabody Picture Vocabulary Test A short form of the Peabody Picture Vocabulary Test PPVT III test designed to measure a child s knowledge of the meaning of spoken words and his or her receptive vocabulary for Standard American English was developed for use in the study This adaptation is based on work done in the United States for the Head Start Impact Study with a number of changes made for use in Australia Different versions of the PPVT containing different although overlapping sets of items of appropriate difficulty were used for the children when aged 4 5 years 6 7 years and 8 9 years A book with 40 plates of display pic
4. The Longitudinal Study of Australian Children An Australian Government initiative Data User Guide November 2013 4 3 Australian Government m4 Australian Institute of Family Studies CONTENTS sccscscssssscsssrsssssenscsssscsscssssessenevsesesseseessesesseees ERROR BOOKMARK NOT DEFINED 1 ABBREVIATIONS vivsissccssssscassssceccesssecssessccdssssenssesssbasesoosdesstetes soos scdansocscsbessoosdbuseeteoeed es 4 2 ACKNOWLEDGEMENTS AND CITATION cccsssscsssssscssssccccssssccssssscscssssccessccecesenssecesssees 6 3 INTRODUCTION ipee 7 4 WHAT IS CSAC o eee ossa Sene oaie dua Se eee tos eee ea 8 AVL OBJECTIVES iet etie eec eee etie certet te ete pecie de edel 8 42 WHOISINVOLEVED oc fcc ces 8 473 TIMBLINES ih eet ete rere eet nen ete etie terere edd ete 8 STUDYINEORMANTS 9 45 MOTHER FATHER DA TA a a a A e n a e 9 5 INSTRUMENTS eee esce O osdesvesedeescesestubveseiseteosebestesncessdesestvivesatessvebestestecesoeses 10 S CHIED ASSESSMENTS eere eter e eere EE OPE ener ex e E RR EET OE ed ea eve Ee TU 13 32 RESPONSERATES rene e er ee TCR TRE 16 6 THE LSAC DATA RELEASE s csccocsscssssssestocssisscossssscisseececsesvssecsesniesescbescssesensesdecsessssescosessassoosss 20 F
5. 1 amp 4 Wave 4 cross sectional analyses and longitudinal analyses pe es ens en involving Waves 1 amp 4 ooo fweights Sample 1 amp 4 _ Wave 4 cross sectional analyses and longitudinal analyses EN SENE e MOONEE involving Waves 1 amp 4 NN RE dfwt Population Longitudinal analyses involving K 1 284 Waves 2 3 amp 4 or Waves 1 2 ample ee a eee LSAC Data User Guide November 2013 efwts K Sample defwt K Population 1 2 3 amp 4 _ defwts K Sample 1 2 3 amp 4 gweight K Population 1 amp 5 ongitudinal analyses involving i Waves 2 amp 4 or Waves 1 2 amp 4 Longitudinal analyses involving Waves 3 amp 4 or 1 3 amp 4 Longitudinal analyses involving Waves 3 amp 4 or Waves 1 3 amp 4 Longitudinal analyses involving Waves 2 3 amp 4 or Waves 1 2 Longitudinal analyses involving Waves 2 3 amp 4 or Waves 1 2 Wave 5 cross sectional analyses and longitudinal analyses i involving Waves 1 amp 5 68 Variable Cohort Type Waves cases Used for name responded to gweights K Sample 1 amp 5 _ Wave 5 cross sectional analyses and longitudinal analyses des delving Waves amp 4 defewt Population 2 3 4 amp Longitudinal analyses involving 5 Waves 2 3 4 amp 5 Waves 1 TM RE O E defgwts Sample 2 3 4 amp L
6. 3 5 and 4 5 The key features of the initial sample design and methodology for each wave are included in this section A full description of the sample design is given in LSAC Technical Paper No 1 and details of the weighting and non response analysis are given in Technical Papers no 3 5 and 6 www aifs gov au growingup pubs technical index html 12 1 Sample design A two stage clustered sample design was employed first selecting postcodes then children with the clustered design allowing analysis of children within communities and producing cost savings for interviews Stratification was used to ensure proportional geographic representation for states territories and capital city statistical division rest of state areas The sample was stratified by state capital city statistical division balance of state and two strata based on the size of the target population in the postcode Postcodes were selected with probability proportional to size selection where possible and with equal probability for small population postcodes Children from both cohorts were selected from the same 311 postcodes Some remote postcodes were excluded from the design and the population estimates were adjusted accordingly Children were selected with approximately equal chance of selection for each child about one in 25 Apart from some remote areas the sample was selected to be representative of all Australian children citizens and permanent reside
7. DR sample of 526 families was recruited to test the content and processes intended for the main waves of the study Over 1000 children were initially selected from 25 postcodes in Victoria Sydney and rural remote New LSAC Data User Guide November 2013 56 South Wales and Queensland Postcodes in Victoria were selected at random but the other postcodes were selected as areas that may provide challenges to the data collection process Wave 1 DR August November 2003 526 families interviewed Wave 2 DR September November 2005 423 families interviewed Wave 3 DR July October 2007 420 families interviewed Wave 4 DR July October 2009 387 families interviewed Wave 5 DR July August 2011 451 families interviewed After each DR both processes and content have been refined to increase efficiency and reduce the time in the home 12 3 Data collection 12 3 1 Interview length Details of the instruments administered each wave are given in the Content of Each Wave section In Wave 1 an average of 126 minutes was allowed for time in the home by the interviewer In home data collection with the B cohort averaged about 1 72 hours while interviews for the cohort averaged about 2 2 hours In Wave 2 although an average of 90 minutes had been allowed for the time in the home the actual time was shorter averaging 66 minutes for the B cohort and 85 minutes for the K cohort In Wave 3 an average of 100 minutes in the home
8. NAPLAN data Data from the instruments are presented in the following order FCF Wave 1 files only 4L MT i PONO NU File names in this section for the general release datasets see confidentialisation section below users of the in confidence data should substitute ic for gr in the file names LSAC Data User Guide November 2013 21 F2F P1D except Wave 1 files PIL except Wave 3 and 4 files P2L PLE except Wave 1 files Teacher Carer Questionnaire Wave 1 5 data Wave 1 files only A number of derived variables are included in the output dataset alongside the raw responses used in their derivation Additionally the main datasets contain status variables e g date of interview whether each type of form was returned etc ABS Population Census and NCAC data and weights 7 11 Australian Bureau of Statistics Census of Population and Housing data Public data from the Australian Bureau of Statistics Census of Population and Housing have been added to the file to enhance the range of neighbourhood characteristics available for analysis with the LSAC data Census data is available for the child s residence at Waves 1 1 5 2 2 5 3 3 5 4 and 5 The items currently included are SEIFA rounded off to the nearest 10 for on the general release file Remoteness Area Classification Percentage of persons aged under 5 10 and 18 years Percentage of persons born in Australia Percentage of person
9. cohort dpa01a Wave 3 cohort epaOla Those items of information that do not change e g details of birth age began or stopped something etc are given the age indicator z so that they have a consistent variable name across cohorts regardless of the age of the child when the information was obtained For example zhs03a indicates birth weight of the study child regardless of whether the information was collected when the child was aged 0 1 years as for the B cohort or aged 4 5 years as for the K cohort LSAC Data User Guide November 2013 33 7 3 2 Topic indicator alpha The topic indicator is taken from the topic field of the data dictionary An effort was made to make abbreviations used meaningful e g family demographics is fd A list of topics and their abbreviations is in Table 4 Table 4 Topics used in LSAC datasets Environment Abbreviation Topic Scope fd Family Demographic information relating to the family Demographics such as education ethnicity and religion fn Finances Financial information such as income and use of government benefits gd General Scales which contain items from multiple Development domains of child development hb Health Behaviour Behaviours and other risk factors that potentially and Risk Factors impinge upon the health of the Study Child or his her family Includes behaviours such as parental smoking and drinking as well as risk factors such as a parent experiencing di
10. is for teacher e The 7 character indicates the subscale 4 for Conduct 5 for Peer Note Also available as part of the SDQ are 1 for Prosocial 2 for Hyperactivity and 3 for Emotional e The final character uniquely identifies each item Note that different items were used for the Conduct subscale in Waves 1 and 2 due to the change in the child s age Table 6 Variable names of SDQ conduct and peer problems subscales Wavel Wavel Wave2 Wave2 Parent1 Teacher Parentl Teacher Kcohort Kcohort cohort cohort name name name name Conduct Problems l Often loses temper cse03a4a cse03t4da dse03a4a dse03t4a EORR OORO Often fights with other children or bullies them Steals from home school or elsewhere Peer Problems Rather solitary tends to play cse03a5a cse03t5a dse03a5a dse03t5a alone dse03a4g gero D ced e Er AR AT LLL MAL E A EAE MD d ED MM ME E KA LEM M RE LAM MM II E RR LE I M Td _Has at least one good friend cse03a5b cse03t5b dse03a5b dse03t5b Generally liked by other childre seO3a cse03t5c Picked on or bullied by other i cse03a5d 0315 children 0 o ls Gets on better with adults than cse03a5e cse03t5e dse03a5e dse03t5e with other children The SDQ is copyrighted by Robert G
11. Due to the relatively low response in Wave 2 to the mail out questionnaire a change in methodology was introduced in Wave 3 Where Parent 1 provided contact details PLEs were telephoned and asked to respond to a Computer Assisted Telephone Interview CATI The response from PLEs who were approached was very positive Of the 856 PLEs that interviewers attempted to contact interviews were achieved with 675 79 and only 53 6 refused an interview Most of the remaining non response was due to not being able to contact the PLE In Wave 3 the Parent 1 was explicitly asked the permission to contact the PLE Therefore it was easy for the Parent 1 to refuse to provide any information about the PLE or refuse the PLE s participation This meant that no information was obtained for 260 1896 PLEs It is worth noting that while there was no direct question asking the Parent 1 permission to contact the PLE some Parent 1 refused the PLE s participation Table 3 summarises the situation with regard to PLEs in Waves 3 4 and 5 LSAC Data User Guide November 2013 18 Table 3 Waves 3 4 and 5 Information obtained with regard to PLE Wave 3 Wave 4 Wave 5 B K Total B K Total B K Total cohor cohort cohort cohort cohort cohort t PLE identified 5 837 1415 674 878 15522 77 3 911 1684 during P1 interview DUE 346 510 856 439 572 101 537 614 The PLE is considered eligible when 1 the PLE sat
12. For example e bhs12a is whether Parent 1 is concerned about the child s weight bhs12b is whether Parent 1 considers the child to be underweight normal weight somewhat overweight or very overweight The 5th digit of the variable name can also be an informant or subject indicator where a question is asked of or about more than one person The indicators used are aParent 1 b Parent 2 c Study Child m Mother f Father or family home for census data t Teacher carer i In between waves respondent LSAC Data User Guide November 2013 35 For example bhs13a is Parent 1 s rating of their own overall health status bhs13b is Parent 2 s rating of their own overall health status bhs13c is Parent 1 s rating of the Study Child s overall health status bhs13p is the PLE s rating of their own overall health status bhs13m is the Mother s rating of their own overall health status bhs13f is Father s rating of their own overall health status An exception to the above rule is in the area of childcare and education variables with topic indicators pc and tp Here the prefixes a b c d and e are used to mean different things at each wave depending on the options available to the child at that age see Table 5 Table 5 Subject indicators for education and childcare variables Age 0 1 Age2 3 Age 4 5 Age 6 7 Age 8 9 Age 10 11 5 E 2 p 19 1 Main Main Main Main a educational educatio
13. Me Met A T TAS VT ACT BE cohort Male K cohort W2 cohor Female K cohert Female Note there are no respondents from non metropolitan ACT LSAC Data User Guide November 2013 74 Figure 12 Proportion of mothers who completed Year 12 Cohort benchmarks by state and part of state 80 E E E 8 El of mothers completed Year 12 E 10 0 Met Xmet Met Xmet Met Xmet Met Xmet Met Xmet Met Xmet Met Xmet Met NSW QLD SA WA TAS NT ACT E p cohort K cchort Note there are no respondents from non metropolitan ACT Figure 13 Proportion of mothers who speak a language other than English at home Cohort benchmarks by state and part of state 40 35 30 20 2 of mothers speak a LOTE in the home a 2 5 0 Met Xmet Met Xmet Met Xmet Met Xmet Met Xmet Met Met NSW Vic QLD SA WA TAS NT ACT E B cohort MK cohort Note there are no respondents from non metropolitan ACT LSAC Data User Guide November 2013 75 13 6 Sample characteristics To assist in the assessment of the representativeness of the Wave 1 sample selected characteristics were compared with ABS estimates gender state and region were compared with the ABS September 2004 Estimated Resident Population figures the other characteristics were compared with previously unpublished population data from the AB
14. Wave 1 2 k cohort Wave 2 3 r K cohort Wave 3 4 eK cohort Wave 4 5 M o Percentage o 5 Number of Months between Interviews Chart Area 13 5 Cross cohort comparisons It should be noted that the two cohorts of LSAC were selected and weighted to represent similar but different populations For the B cohort the reference population LSAC Data User Guide November 2013 73 is 0 year old children in Australia in 2004 excluding those from certain remote postcodes while for cohort the reference population is 4 year old children in Australia in 2004 excluding those from certain remote postcodes One implication of this is that the K cohort will have a greater number of children born overseas as there was more time for families to immigrate to Australia between the birth of their child and selection into the study The 2001 census contained 4 446 of 4 year olds that were born overseas compared with 0 8 of O year olds In comparison the weighted percentages for these figures in LSAC at Wave 1 were 4 2 v 0 4 However there are also other demographic differences between the populations that are reflected in the benchmarks used to weight the two cohorts Figure 11 shows the population percentages in each state by part of state by gender stratum for the B cohort and K cohorts The B and K cohort figures generally match closely however the population from which the K cohort was selected was
15. files after cleaning for each cohort for Waves 1 2 and 3 poortudsb0 poortudsb2 etc o One datafile with all cases and no data cleaning performed on them for each cohort for Waves 1 2 and 3 ucdiaryb0 ucdiaryb2 etc o One datafile for K cohort only for Wave 4 tudk10 o One datafile for K cohort only for Wave 5 tudk12 Three Medicare Australia Datasets representing information from the 3 Medicare Australia databases the information was drawn from mbs pbs and acir Two Study Child household composition datasets one for each cohort hhgrb hhgrk Two PLE household composition datasets one for each cohort plehhgrb plehhgrk Two Wave 2 5 datasets one for each cohort Isacgrb3 Isacgrk7 Two Wave 3 5 datasets one for each cohort Isacgrb5 Isacgrk9 LSAC NAPLAN dataset Isacnaplan LSAC MySchool dataset Isacmyschool Note Wave 1 5 datasets have been added to the Wave 1 datasets This is possible because all respondents that responded to Wave 1 5 had to complete a Wave 1 interview This is not the case with other between wave mail outs respondents may have completed any prior combination of interviews This structure has been used to reduce the size of the main datasets and because some data are formatted using more than one record for each child 7 1 Main dataset The main dataset consists of the data from all questionnaires except the Time Use Diary Wave 2 5 Wave 3 5 some household composition information and LSAC
16. in the Survey Methodology section of this guide and in LSAC Technical Paper No 1 Sample Design available from the study website http www growingupinaustralia gov au pubs technical index html 4 4 Study informants The study collects data from multiple informants e Parent 1 P1 is defined as the parent who knows the Study Child best in most cases this is the child s biological mother e Parent 2 P2 is Parent 1 s partner or another adult in the home with a parental relationship to the Study Child in most cases this is the biological father but step fathers are also common e The Study Child themselves e Parent Living Elsewhere PLE is a parent who does not live with the Study Child this is most commonly the biological father after separating from the biological mother This collection was started in Wave 2 e Teachers and childcare workers In addition data are linked to the file from the National Childcare Accreditation Council Medicare Australia the Australian Bureau of Statistics and the National Assessment Program Literacy and Numeracy NAPLAN 4 5 Mother Father data While Parent 1 is usually the mother and Parent 2 is usually the father this is not always the case However many users prefer to analyse the data by parent gender i e Mother and Father rather than Parent 1 and Parent 2 Therefore all the variables collected for both Parent 1 and Parent 2 are presented as Mother and Father va
17. independent moderators Data on 35 principles was collected Each principle was related to one of the ten quality areas Response categories for each principle were Unsatisfactory Satisfactory Good Quality and High Quality Proportionally weighted factor score regression coefficients for principle ratings were calculated to determine the extent to which each principle contributed to a Quality area For further information see Rowe 2006 As no data about the child was obtained no consent was required from parents to collect this data although parents did need to give details of their carers to assist in the linking 7 2 Supplementary files 7 2 1 Time Use Diary data In Waves 1 to 3 responding families were given two Time Use Diaries TUDs to complete at each wave Each record in the TUD data relates to a single diary i e each child can have up to two records one for each TUD The key component of the TUD data is to gather information on children s activities and context for the 96 15 minute periods of each 24 hour block In addition to these LSAC Data User Guide November 2013 24 variables the TUD data includes the child s unique identification number in order to allow linkage with the main dataset It also includes the following general descriptors Date diary should be completed Day of week diary should be completed The diet of the study child on the day in question Waves 2 and 3 The
18. is selected from each postcode included in the survey However the use of clustering violates the standard assumption of independence of the observations that is fundamental to many statistical routines in major statistical packages When children or carers have more similar characteristics within a given postcode than children or carers selected purely at random the responses within postcodes will be correlated This correlation will lead to an increase in the standard errors and size of the confidence intervals The extent of this increase is measured by the design effect which is the ratio of the variance of an estimate from the survey to the variance that would have been achieved by a simple random sample of the same size Failure to account for clustering in the analysis can lead to under estimating the size of standard errors and confidence intervals In some circumstances this can result in misleading conclusions of statistical significance 13 1 3 Weighting The Wave 1 weights provided in the LSAC data files take into account both the probability of selecting each child in the study and an adjustment for non response An analysis of possible differences in the characteristics of respondents and non respondents was undertaken and identified two factors associated with the probability of participating in the survey whether the mother speaks a language other than English at home and whether the mother has completed year 12 Both of thes
19. longitudinal analyses A complete list of LSAC weighting variables is given in Table 11 Table 11 Weighting variables Variable Cohort Type Waves cases Used for name responded to aweight B Population 1 Wave cross sectional analyses _ aweights B Sample MESE Wave cross sectional analyses _ aweightd B Day J loo Wave cross sectional analyses _ bweight Population 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses osc re involving Waves 162 bweights B Sample 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses et eee Re EA Ae involving Waves 162 bweightd B Day 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses S involving Waves amp 2 cweight Population 1 amp 3 Wave 3 cross sectional analyses and longitudinal analyses 4 involving Waves amp 3 cweights B Sample 1 amp 3 Wave 3 cross sectional analyses and longitudinal analyses involving Waves 1 amp 3 LSAC Data User Guide November 2013 66 Variable Cohort Type Waves cases Used for name responded to cweightd B Day 1 amp 3 Wave 3 cross sectional analyses and longitudinal analyses Pee aes a a involving Waves 1 amp 3 bewt B Population 1 2 amp 3 Longitudinal analyses involving ett ae ee Waves 2 amp 3 or Waves 1 2 amp 3 bcwts B Sample 1 2 amp 3 Longitudinal analyses involving
20. possible A two page help sheet is included on the LSAC Data CD to help users learn these conventions 7 3 Questionnaire variables Variable names follow the standard format in most cases Exceptions to this naming convention derived items and household composition variables are explained in sections that follow Standard format A tt XXXXX where A child age indicator tt topic indicator XXXXX specific question identifier 7 3 1 Child age indicator alpha The child age indicator is an alpha symbol that indicates the child s age allowing for comparisons between the cohorts where data has been collected for both cohorts at that age For instance e a indicates the child is aged 0 1 years which is B cohort in Wave 1 e b indicates the child is aged 2 3 years which is B cohort in Wave 2 e c indicates the child is aged 4 5 years which is the B cohort in Wave 3 and the K cohort in Wave 1 e d indicates the child is aged 6 7 years which is the B cohort in Wave 4 and the K cohort in Wave 2 e indicates the child is aged 8 9 years which is the B cohort in Wave 5 and the K cohort in Wave 3 e f indicates the child is aged 10 11 which is the K cohort in Wave 4 etc This is an example of how the child age indicator is used for the item Parent 1 rating of parenting self efficacy Wave 1 B cohort 01 Wave 2 B cohort bpaOla Wave 3 B cohort 01 Wave 1 cohort cpaOla Wave 2
21. relationship of the diary writer to the child Over what duration the diary was completed Actual day and date of completion Hours of work done by respondent on day of completion Waves 2 and 3 What kind of day was described in the diary Due to scanning problems in Wave 1 and other data quality issues that are likely to apply equally across waves a number of imputations and corrections have been applied to the TUD data see Data Issues paper on the study website for details So researchers can determine the effect of these imputations corrections to the data on any analysis An uncorrected version of the TUD data is also provided as well as files containing imputations corrected versions of cases that were considered unsuitable for data analysis even after correction LSAC Technical Paper 4 includes a detailed discussion of issues that should be considered when using the time use data The Technical Paper is available from www aifs gov au growingup pubs technical index html In Wave 4 a new methodological approach was undertaken The study shifted away from the parent being the informant to the study child being the informant In Waves 4 and 5 only the K cohort completed the TUD which was substantially different from the TUDs that the parents completed in earlier waves The TUD in Waves 4 and 5 had the form of an ABS Activity Episode diary This data is stored as a long file as opposed to the wide files the previous diaries were stored
22. represents any combination of letters and characters represents any single character Some examples of the use of these characters are as follows apw23a returns a range of variables apw23ala through to apw23a4b apw23a4 returns two variables apw23a4a and apw23a4b pw23a4a shows if this variable exists over different waves apw23 4a shows if this variable exists for different people in the same wave pw23 4a shows if this variable exists for different people in different waves LSAC Data User Guide November 2013 48 8 3 3 Some useful tips navigating the Data Dictionary Only items currently on the main datasets are included in the data dictionary The User Guide provides information on the composition of other datasets Items on the data dictionary are in the same order as on the data files but can easily be sorted into other orders for example grouping topics Searching the on line data dictionary finds whole words e g searching for child won t find children as well However an asterisk will represent any combination of characters So searching for child will find child children childcare etc The introduction page for the data dictionary contains a list of topics and constructs that can be used for finding the information you want The Question ID field gives the variable name without any wave or person indicators Filtering by this field is the best way to tell which questions were
23. returned then teacher s responses for this hicid are set to 9 To identify cases for which a form was not returned or consent was not provided a data user can use an indicator variable see Table 1 for details c one of the informants refused to participate e g if a parent refused to participate but not a child then parent s responses are set to 9 To identify cases when the parent refused to participate a data user can use nopar indicator variable d a form was partially completed e g parent 1 completed the interview over the phone but face to face component did not occur To identify these cases a data user can use partresp indicator variable see 7 8 for more detail Negative income loss Missing data data not collected where it might be expected e g the respondent skipped a question they should have answered in a self complete form or made missing due to an unreliable value e g weight of Parent 1 recorded as 800kg 44 3 Documentation A number of tools can be used to navigate the LSAC dataset Marked up instruments Frequencies Online LSAC Data Dictionary Excel spreadsheets of the Data Dictionary good for creating hardcopies Users should also consider which documents they want to print out and which they want to look at electronically We have found that the marked up questionnaires and interview specifications are best printed and provide the easiest method of browsing to f
24. the data are kept and there must be tamper evident barriers to access i e if there were a break in it would be obvious from broken glass damaged lock etc e If you have an individual license and you change employers you MUST inform DSS prior to doing so Data MAY be able to move with the individual depending on the research to be undertaken and the new employer You must NOT leave the data with your old employer if you move e If you change your research project you MUST seek permission to use the data for the new project from DSS 6 1 2 How data files are provided All data are provided in three formats SAS SPSS and STATA however users can transfer the data to other formats if they wish The CD ROM and or website also includes extensive data documentation including this document marked up questionnaires and variable frequencies The data files and the other documentation are discussed in detail in later sections of this document LSAC Data User Guide November 2013 20 7 File structure For the Wave 5 data release the following datasets are available Ten datasets comprising the main datasets for each wave and cohort Isacgrb0 Isacgrb2 Isacgrb4 Isacgrb6 Isacgrb8 Isacgrk4 Isacgrk6 Isacgrk8 Isacgrk10 and Isacgrk12 20 Time Use Diary datasets o One cleaned datafile with problematic cases deleted for each cohort for Waves 1 2 and 3 diarybO diaryb2 etc o One datafile with the cases deleted from the above
25. to previous versions of the Data User Guide These will be added to as other issues are addressed The current set of papers includes e Issues Paper no 1 Cleaning of Time Use Diary Data e Issues Paper no 2 Report on Adapted PPVT III and Who Am I e Issues Paper no 3 Imputations to solve missing data problems in Wave 2 5 e Issues Paper no 4 Investigation of Educational program type cpc06a4 in Wave 1 e Issues Paper no 5 Cleaning of income data e Issues Paper no 6 Height differences e Issues Paper no 7 Data issues in Wave 3 5 e Issues Paper no 8 Data issues in Wave 4 e Issues Paper no 9 Data issues in Wave 5 Other important issues are addressed below 13 1 Weighting and external validity The LSAC study design based on a complex probability sample is specifically designed to produce valid estimates at the population level Unlike clinically based or convenience samples the LSAC sample is population based by design By properly accounting for the survey design when analysing the data it is possible not only to make inferences about the children and families participating in the study but to make valid inferences about the entire population of children in the relevant age groups The LSAC sampling strategy has three important elements that distinguish it from a simple random sample SRS stratification to ensure proportional representation of all states and both capital city and ex metropolitan areas e clustering by po
26. training teams were used comprising staff from both AIFS and ABS This time AIFS staff undertook the direct assessment training after receiving training from a child psychologist the use of Computer Assisted Interviewing for the direct assessments helped ensure the consistent administration of these assessments For Wave 3 176 interviewers from ABS were trained in a series of 2 day training courses in Brisbane Melbourne Sydney and Perth during March and April 2008 Interviewers who had not worked on LSAC previously were given background training in LSAC before the 2 day course commenced Two training teams were used comprising staff from the ABS AIFS and DSS Again AIFS staff undertook the direct assessment training For Wave 4 181 interviewers from ABS were trained in a series of 3 day training courses in Brisbane Melbourne Sydney and Perth Two training teams were used comprising staff from the ABS AIFS and DSS As in previous waves AIFS staff undertook the direct assessment training For Wave 5 198 interviewers from ABS were trained in a series of 3 day training courses in Brisbane Melbourne Sydney Adelaide and Perth New to LSAC interviewers defined as anyone who did not participate in Main Wave 4 attended the first day of classroom training where topics such as Background to the Study Physical measurements Direct Assessments and Notebook security were covered All Interviewers attended Days 2 and 3 w
27. was allowed for time in the home the actual time was 91 minutes for the B cohort and 98 minutes for the K cohort In Wave 4 an average of 110 minutes in the home was allowed for time in the home the actual time was 102 minutes for the B cohort and 108 minutes for the K cohort In Wave 5 an average of 110 minutes in the home was allowed for time in the home the actual time was 98 minutes for both cohorts 12 3 2 Interviewers As part of standard ABS interviewer induction ABS interviewers receive two weeks of intensive training across a range of standard procedures and practices All interviewers received 8 hours of home learning Computer Based Learning module Home Study Exercises reading of Interviewer Instructions In Wave 1 150 interviewers and field supervisors from I view were trained during a series of 4 day sequential training courses conducted in Melbourne Brisbane Perth and Sydney during February to early March 2004 The principal trainers were the same for all courses ensuring consistency in training Psychologists conducted the training for the Who am I the PPVT and the interviewer observations A large part of the training involved practice interviews with one day devoted to interviews with parents and children For Wave 2 147 interviewers from ABS were trained in a series of 3 day training courses in Sydney Melbourne Brisbane and Perth during March and April 2006 LSAC Data User Guide November 2013 57 Two
28. 0 766 723 75 5 58 2 584 language other acre erc occu poc c E Ce LUE Mother didnot 1688 2044 848 86 6 788 81 7 73 2 771 704 734 complete Yr 12 Father did not 1890 2016 90 0 90 0 85 9 87 0 77 0 80 703 722 complete Yr 12 New South 1615 1573 90 3 90 2 844 863 796 80 3 77 6 76 9 Wales Victoria 1251 1245 884 86 3 85 1 860 839 814 78 1 74 4 Queensland 1054 988 914 90 8 88 0 87 2 87 1 885 866 86 2 South Australia 347 339 91 1 894 88 2 86 7 83 3 844 79 5 80 2 Western 533 507 897 915 83 9 87 6 807 852 77 7 80 5 Australia Tasmania 113 136 90 3 941 92 0 912 1018 956 947 94 1 Northern 87 82 90 8 89 0 83 9 87 8 563 732 517 67 1 Territory Australian 107 113 297 2 94 7 95 3 947 991 93 8 925 92 9 Capital Territory Capital City 3194 3095 906 89 3 86 2 868 804 809 76 4 77 0 Statistical Division LSAC Data User Guide November 2013 77 Wave 1 N responding responding responding responding to Wave 2 to Wave 3 to Wave 4 to Wave 5 Characteristics K B K B K B K B K Full sample 5107 4983 90 2 89 6 85 9 869 834 83 6 80 0 79 4 Balance of state 1913 1888 896 90 0 85 4 872 869 877 85 7 83 2 14 User support and training User training sessions are offered by AIFS to further develop the information provided in the user manual and to allow users to interact with the LSAC Data Management team and benefit from their knowledge and experience with the data These sessions consist of an introduction to LSAC and the newly released datasets inc
29. 14 Date stopped living with study child 15 Reason stopped living with study child 16 Temporarily away from home as Wave 2 question 160 Temporarily away from home other as per Wave 2 question 17 Has a condition or disability for 6 months or more as per Wave 2 question 17a Has sight problems as per Wave 2 question 17b Has hearing problems as per Wave 2 question 17c Has speech problems as per Wave 2 question 174 Has blackouts etc as per Wave 2 question 17 Has difficulty learning as Wave 2 question 17f Limited use of arms or fingers as Wave 2 question 17g Difficulty gripping as per Wave 2 question 17h Limited use of legs and feet as per Wave 2 question 171 Other physical condition as per Wave 2 question 17j Other disfigurement as per Wave 2 question 17k None of the above conditions as per Wave 2 question 18 Restricted in everyday activities 18a Has difficulty breathing as per Wave 2 question 18b Has chronic pain as per Wave 2 question 18c Has nervous condition requiring treatment as per Wave 2 question 184 Has mental illness requiring supervision as Wave 2 question 18e Has head injury as per Wave 2 question 18f Has other long term condition as per Wave 2 question 18g Has other condition requiring treatment as per Wave 2 question 18h None of the above restrictions as per Wave 2 question 19 Date began living with the study child Household member was in the household for at least
30. 3 months but moved in 20 and left between current and previous wave LSAC Data User Guide November 2013 40 7 6 PLE Household composition variables From Wave 4 the household information for the child s parent living elsewhere PLE has been collected PLE household composition variables have a similar structure to that of the Study Child Household composition variables A f xple Where A Child age indicator f f for family Question number numeric Sub question indicator optional ple person identifier within PLE household with ple for Parent Living Elsewhere and member number Note that e The age indicator as described in section 7 3 1 e f is a constant to indicate that it is the household composition that is being described e The question number and sub question indicator indicate the question being responded to e The person identifier comprises the constant ple to indicate that it is PLE household and the member number For every PLE household the Study Child is Member 1 plel and PLE is Member 2 ple2 For example variable f02ple2 refers to a PLE gender when a Study Child is 10 to 11 years old Any additional member in the household is assigned a PLE member number that remains the same throughout the study even if they leave and re enter the PLE s home Table 8 shows the information that is available for each PLE Table 8 Question numbers used in variable names for PLE hou
31. 5107 24242 82 4983 4164 84 CASI 4242 4210 99 4164 4116 99 l 3706 2677 T2 3512 2645 75 CSR l 4242 4181 99 NA ACASI l N A NA 4169 4094 99 TUD N A NA NA 4169 3994 96 l 4242 4185 99 NA MR 4242 4180 99 lt 4169 4103 99 PLE CATI 439 377 86 572 493 86 TQ 4143 3427 83 4025 3352 83 B cohort K cohort Wave 5 Eligible Eligible Actual Instrument a b Actual c b c F2F d 5107 4085 80 4983 3956 79 CASI 4077 4010 98 3952 3857 98 P2L 3512 2444 70 327 2333 CSR 4026 4014 100 3872 3850 99 ACASI N A N A 3873 3844 99 TUD N A NA 387 1 3649 94 PPVT 4026 8397 99 N A NA NA MR 4027 3985 99 N A NA NA PLE CATI 537 404 O75 614 464 76 TQ 4021 3490 87 3857 3225 84 D Represents instances where a child interview was completed and the main interview with the parents was not Specifically in Wave 4 there were five cases K cohort and in Wave 5 there were eight cases for the K cohort and four cases for the B cohort N A Not administered a Questionnaire acronyms are detailed in previous section b Eligible means the number of LSAC children for whom a questionnaire was applicable e g children are eligible for an HBC questionnaire if the child s main care is attended for 8 hours or more per week and this is home based care c Actual means the number of respondents for whom a form was re
32. 9 of eligible respondents This is higher than the response rate of 88 of eligible respondents achieved in Wave 3 using the self complete form In Wave 5 response rates are very similar to response rates obtained in Wave 4 This is due to no mode changes and attrition tapering off 5 2 2 Parent 2 TUD and Teacher forms Response rates to the P2L and the TUD were broadly similar between waves Wave 1 2 and 3 while the carer and teacher questionnaire response rates were much improved in Wave 2 with similar response rates at Wave 3 In Wave 4 the TUD response rate was 96 The higher response rate could be contributed to the change in the procedure and the informant In Waves 4 and 5 the interviewer collected the TUD information from the child not the parent as part of the interview rather than leaving a diary which then had to be completed and mailed back by respondent families after the visit 5 2 3 PLE response The PLE questionnaire was introduced in Wave 2 and applies for children who see their parent living elsewhere at least once a year There are three stages where non response can occur 1 obtaining contact details from Parent 1 2 obtaining permission from Parent 1 and 3 receiving a response from the PLE In Wave 2 contact details were given for 6946 of cases for the B cohort and 7096 of cases for the K cohort and responses received from 35 of PLEs sent a questionnaire for the B cohort and 47 for the K cohort
33. Al N A NA N A 4983 4880 98 N A 4983 4382 88 HBC 788 842 243 N A N A CBC 436 5233 253 N A NA N A TQ N A NA NA _ 4761 3276 69 N A NA N A 1366 720 93 W1 5 5061 3573 71 4935 3594 73 B cohort K cohort Wave 2 Instrument a Eligible b Actual c Eligible b Actual c F2F d _ 5107 4606 90 4983 4464 90 PID 4606 4504 298 4464 4358 98 PIL _ 4606 3536 TI 4464 3495 T8 4099 3128 276 3804 2949 78 TUD 1 4606 _ 3477 275 4464 3446 TUD 2 4606 3459 75 4464 3460 78 PPVT N A 4464 4409 99 MR N A 4464 4402 299 PLE Mail out 400 96 24 612 199 33 HBC 791 1533 267 NA CBC 1672 1144 68 N A N A TQ _ N A 4447 3632 292 W2 5 5107 3246 64 4983 3252 65 B cohort K cohort Wave 3 Eligible Actual Eligible Actual Instrument a b c b c F2F d 5107 f 4386 86 4983 4331 87 PID l 4386 3831 87 4331 3807 88 l 3900 2753 71 3707 26800 7 TUDI l 4386 2959 67 4331 2961 68 TUD2 4386 2950 67 4331 2963 68 l 4386 4266 97 4331 4273 99 WAI 4386 4197 9 NA MR N A l N A NA 4331 4270 99 PLE CATI 346 272 TI 510 403 79 TQ 4114 3395 834 4275 3643 85 LSAC Data User Guide November 2013 16 B cohort K cohort Wave 4 Eligible Eligible Actual Instrument a b Actual c b c F2F d
34. Computer Computer Study Child Need consent K K Assisted Interview from ACASI P1 id40e amp SC id40f Time Use Diary Paper Parent 1 N A BK BK BK TUD Time Use Diary Computer Study Child Need consent K K TUD from P1 id40i amp SC id40j Parent Living Paper PLE plescd BK Elsewhere PLE mailed out Parent Living Computer Te PLE plescd BK BK BK Elsewhere PLE lephone CATD Home Based Carer Paper Carer hbccbc B B HBC Centre Based Carer Paper Carer hbccbc B B LSAC Data User Guide November 2013 10 Teacher Questionnaire Paper Teacher tcd K K BK BK BK TQ Physical Computer Study Child Need consent BK BK BK BK BK Measurements PM from 1 id30d amp SC id30e Who Am I WAT Computer Study Child cid44al K B PPVT Assessment Computer Study Child ppvtd K K BK B B PPVT Matrix Reasoning Computer Study Child id44al K K BK B MR Study Child Blood Computer Study Child Need consent K K Pressure BP from P1 id47a amp SC id47b Interviewer Computer Interviewer BK BK BK BK BK Observations IOBS NB 1 The indicator variable can be used to see if data 15 present or not for a particular instrument for more information see sections 7 8 amp 7 9 2 The in the indicator variable should be replaced by the age indicator a c d e f or g a
35. ERVIEW Sous o rete es ay tee e P ee vete ds e Ea eee aee eet d 71 13 4 TIME BETWEEN INTERVIEWS 0 cccccccccccccccccccecececccccccceccseecececccscsesescesececscseececscesesscecsseseeesesesees 73 13 5 CROSS COHORT COMPARISONS ccccccecececececccecescecsccccecccececccesesesescsesescececesececevecesececeseveveceesess 73 13 6 SAMPLECHARACTERISTICS nete e rehenes tes cs ce e eee usus cet eo cobdes eo d Eee aeu eue eg 76 1 5 Data User Guide November 2013 2 14 USER SUPPORT AND TRAINING cccssssssssessssesssssessssersesessersesesserssnesesssesessassesessessesessens 78 ONLINE ASSISTANCE 2 2 ees ecce e exe o rere hera te ea eU es EC Meets Reve MEE te o Ov d 78 14 2 GETTING MORE INFORMATION 78 15 REFERENCES AEN eae eeu deuves EAA ENI a easi oup duo 79 16 BIBLIOGRAPHY 80 LSAC Data User Guide November 2013 3 1 Abbreviations ABS Australian Bureau of Statistics ACARA Australian Curriculum Assessment and Reporting Authority ACIR Australian Childhood Immunisation Register AEDI Australian Early Development Index AIFS Australian Institute of Family Studies ANUA Australian Nation University ranking of occupational prestige 4 edition ASCL Australian Standard Classification of Languages ASCO Australian Stan
36. ILE STRUCTURE OPER 21 Top MAN DATASET 5a arreter bi e tee eter bet eee E Meee te ee P eue ERE ts 21 41 2 SUPPLEMENTARY FILES esee tae e eter 24 7 3 QUESTIONNAIRE VARIABLEG cccesssccesssscesssseccecessseceessnsecsesaececessecssesaesecseaaececessseceesasecseaaaeers 33 7 47 DERIVED VARIABLES eerie ere reete ea ee e ec ei ser iE 37 7 5 STUDY CHILD HOUSEHOLD COMPOSITION VARIABLES eee eene nennen nennen nnne en 38 7 6 PLE HOUSEHOLD COMPOSITION VARIABLES eterne 41 7 7 AGEINVARIANT INDICATOR 42 7 8 INDICATOR VARIABLES eet teet ee ip ege eee ep er ice i to EE 42 7 9 VARIABLE LABELLING 43 7 10 MISSING VALUE CONVENTIONS ccccccccccccccccccscecececccscscecscsescscscscscseseecececeesescscecesecscecesecesecssess 44 8 DOCUMENTATION 45 8 1 MARKED UP INSTRUMENTS ccccccccscsesesessesssseseseeesesesesesesesesesecseseseesesesesesesecesesesecesesseseesesenens 45 82 EREQUENCIES aede a eese eed Gee ceded ere ure pee ed ude pea o P RET ERE 46 8 31 DATA DICTIONARY teeth er nte eret ater ber I 46 9 DATA TRANSFORMATIONS 50 9 1 TRANSFORMATIONS TO ENSURE CONSISTENCY ccccccccccccccscscscscecececeescscscsesesescecscesseseeceseceseeeeees 50 9 2 TRANSFORMATIONS TO UPDATE INFORMATION cccccccc
37. L Parent 2 Self Complete Questionnaire PBS Pharmaceutical Benefit Scheme PLE Parent Living Elsewhere PPVT Peabody Picture Vocabulary Test Peabody Picture Vocabulary Test 3 Edition QIAS Quality Improvement and Accreditation System for Long Day Care centres RSE Relative Standard Error SACC Standard Australian Classification of Countries SEIFA Socio Economic Indexes For Areas SRS Simple Random Sample TIS Telephone Interpreter Service TUD Time Use Diary WAI Who Am I WISC Wechsler Intelligence Scale for Children LSAC Data User Guide November 2013 5 2 Acknowledgements and citation The current version of the LSAC Data User Guide has been updated by AIFS The Wave 5 data files were prepared by the ABS and AIFS Readers wishing to cite this document should use the following form of words Australian Institute of Family Studies 2013 Longitudinal Study of Australian Children Data User Guide November 2013 Melbourne LSAC Data User Guide November 2013 3 Introduction This Data User Guide is designed as a reference tool for the users of the Growing Up in Australia the Longitudinal Study of Australian Children LSAC datasets It aims to cover all of the things you need to know to use the LSAC data such as an overview of the survey methodology an outline of the file structure variable naming conventions and issues data analysts need to be aware of The followi
38. S 2001 Census of Population and Housing see Table 12 Table 12 Wave 1 sample characteristics compared with ABS data B cohort K cohort LSAC ABS LSAC ABS Gender Male 51 2 51 3 50 9 51 3 Female 48 8 48 7 49 1 48 7 Family type Two resident parents guardians 90 7 88 1 86 0 82 0 One resident parent guardian 9 3 119 14 0 18 0 Siblings Only child 39 5 362 11 5 12 1 One sibling 36 8 35 6 48 4 45 9 Two or more siblings 23 7 28 2 40 1 42 0 Ethnicity Study child Indigenous 4 5 43 3 8 4 3 Mother speaks a language other than English at home 14 5 16 8 15 7 17 6 Educational status Mother completed Year 12 66 9 56 6 58 6 48 3 Father completed Year 12 58 5 50 2 52 7 45 3 State New South Wales 31 6 34 1 31 6 33 7 Victoria 24 5 24 6 25 0 23 8 Queensland 20 6 19 3 19 8 19 7 South Australia 6 8 68 6 8 T2 Western Australia 10 4 9 9 10 2 10 1 Tasmania 2 2 d 2T 2 5 Northern Territory 1 7 1 4 1 7 1 6 Australian Capital Territory 2 1 17 23 1 3 Region Capital City Statistical Division 62 5 63 7 62 1 62 1 Balance of state 37 5 26 3 37 9 37 9 Total 5047 4983 Note ABS 2001 Census for families for 0 and 4 year olds except where based on September 2004 Estimated Resident Population for families of 0 and 4 year olds For most characteristics the Wave 1 sample is only marginally different to the ABS data The largest difference is in the educational status of the parents Children with mothers who have completed Year 12 are over represented
39. Waves 4 and 5 a laser stadiometer was used Two measurements were taken and if the two measurements differ by 0 5cm or more a third measurement was taken The average of the two closest measures is included on the data file 5 113 Girth This measurement is taken for children aged 2 years and older using non stretch dressmaker s tape positioning the tape horizontally over the navel Two measurements were taken and if these differed by 0 5cm or more a third measurement was taken The average of the two closest measures is recorded on the data file 5 114 BodyFat A body fat measurement was included in Waves 4 and 5 with the reading provided by the same scales used for weight Tanita Body Fat scales Issues with the body fat measurement are outlined in the Issue Paper series 5 11 5 Head circumference This measurement was only taken for the B cohort in Wave 1 using an Abbott head circumference tape Two measurements were taken and if these differed by 0 5cm or more a third measurement was taken The average of the two closest measures was included on the data file LSAC Data User Guide November 2013 13 5 1 1 6 Blood pressure This measurement was taken for the K cohort in Waves 4 and 5 using A amp D Digital Blood Pressure Monitor Model UA 767 Two measurements were taken by the interviewer with a one minute interval between the measurements Both of the readings are included in the data file 5 1 2 Who am I WAD
40. a User Guide November 2013 42 data for the sections where parent 1 is the informant To identify these cases data user can use the following indicator variable nopar refers to the age indicator Another example is teacher s responses To identify cases where a teacher form was not returned a data user can examine the variable A data user can also examine the following indicator variables partresp to identify cases that were incomplete due to an interview stopping half way as opposed to just certain sections being refused or hhresp to identify cases where the household interview was completed There are a large number of indicator variables and data users are encouraged to investigate the reasons for data being incomplete through these variables Note that the indicator variables do not follow the general variable naming conventions described above Some indicator variables are listed in Table 1 Indicator variables can be found in the data dictionary under the topic Identifiers along with other variables that fall under that topic For more information refer to the data dictionary 7 9 Variable labelling convention The labels used for the variable dataset take the following general form Age Informant Subject Questionnaire Position Construct Label Age is a label for the age indicator from the variable name so a 0 1 b 2 3 c 4 5 e d 6 7 If no age indicator is present in the variable
41. a little more likely to live in capital cities 66 5 v 63 6 Figure 12 shows the population proportions for mothers having completed Year 12 by state and part of state for each cohort The B cohort population was more likely to have completed Year 12 in every part of the country with the ABS Census figures nationally being 56 696 for the B cohort against 48 396 for the K cohort Figure 13 shows the populations proportions for mothers speaking a language other than English at home by state and part of state for each cohort These proportions were more closely matched between the B and K cohorts The implication of this is that just because the two cohorts have been weighted using similar variables it does not mean that the variables that they have been weighted on are not responsible for the differences observed between the two For example because the two cohorts have had non response due to maternal education adjusted for it does not mean they will have equal proportions of mothers who had completed Year 12 when the weights are applied Therefore different levels of maternal education could explain differences observed between the two samples in the educational attainment of children Figure 11 Cohort benchmarks by state part of state and gender 14 12 10 8 6 T T T Met Xmet Met Met NSW vic QLI of population by cohort o Xmet at xmet Met Xmet Met Xmet in
42. abetes during pregnancy he Home Education Information on factors likely to impinge on the child s learning while at home such as parental support for education number of books in the home and TV use Also contains information on parent interaction with teachers such as parent teacher interviews even when asked from the teacher s perspective pl Elsewhere Parental Leave in Australia ho Housing Information on housing such as number of bedrooms tenure type and payments hs Health Status Information about the physical and mental health status of the study child or his her family such as Body Mass Index diagnosis with conditions and number of hospital stays id Identifiers Questionnaire process variables such as sequence guides consents and details of proxy respondents Ic Learning and Information on the child s development in the Cognition areas of learning and cognition including Outcomes language literacy and numeracy pa Parenting Information on parenting styles and other information effecting parenting such as self efficacy pe Program Characteristics of the educational or childcare Characteristics program such as type of program number of days or hours the child attends and staff satisfaction pe Parent Living Details of the child s PLE such as the relationship to study child interactions with resident parents and child support Data from the Parental Leave in Australia Ne
43. alculated When undertaking longitudinal analysis involving the Outcome Index analysts should be cautious with using outcome indices from different waves in a pooled data file as they can use different measures at different waves to create the sub domains LSAC Data User Guide November 2013 51 10 Confidentialisation Two types of data are available to data users In confidence data General release data 10 1 In confidence data The only information not included is name address and other contact details for the child family childcare agency and teacher or carer Access to the in confidence datasets may be granted where data users are able to demonstrate a genuine need for the additional data and that they meet the necessary additional security requirements 10 2 General release data In addition to the information removed for the in confidence file some other items have also been removed and some items have either been transformed had response categories collapsed or have been top coded i e recoding outlying values to a less extreme value The following items are removed Qualitative data provided by respondents Census and postcode data for the location of carers and schools The following items are transformed Postcode postcodes are given an indicator so that all children selected in the same postcode can be identified Date left hospital after birth number of days between birth and departure The foll
44. amiliarise yourself with the data available The Data Dictionary is best used for searching for specific items and mapping items from wave to wave These tools are described in more detail below 8 1 Marked up instruments The associated variable name has been added beside each question in the questionnaires and interview specifications Derived variables are also included See Figure 2 for an example Figure 2 Example of the marked up questionnaires 8 Sometimes family members may have difficulty 9 Which best describes the degree of happiness getting along with one another They do not all things considered in your relationship always agree and they may get angry In general how would you rate your family s ability Perfectly happy i to get along with another ee eee BE Reyne NCMO SERE TRUE ems uM EB pcc eee Seis Extremely Notin a relationship EP Goto Question 11 A mock questionnaire interview specifications has also been generated for the CAI instrument used in Waves 2 3 4 and 5 Figure 3 is a sample of this LSAC Data User Guide November 2013 45 Figure 3 Example of Wave 2 interview specification B4 hs13 B5 4 1514 Show Prompt Card 9 Does lt NameSC gt need or use more medical care mental health or educational services than In general how would you say lt NameSC s gt is usual for most children of the same age current health is 1 Ye
45. amp 5 or Waves 1 ee ee iE 2X O src dicet ae bcdewts Sample 1 2 3 4 Longitudinal analyses involving amp 5 Waves 2 3 4 amp 5 or Waves 1 23465 s cweight K Population Wave cross sectional analyses _ cweights sample Bolo y Wave cross sectional analyses _ cweightd K eee NEN Wave 1 cross sectional analyses dweight Population 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses involving Waves amp 2 LSAC Data User Guide November 2013 67 Variable Cohort Type Waves cases Used for name responded to dweights Sample 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses M HP involving Waves 1 amp 2 dweightd K Day 1 amp 2 Wave 2 cross sectional analyses and longitudinal analyses ec D n EL involving Waves1 amp 2 eweight Population 1 amp 3 i Wave 3 cross sectional analyses and longitudinal analyses eweights K Sample 1 amp 3 Wave 3 cross sectional analyses and longitudinal analyses involving Waves 163 Wave 3 cross sectional analyses and longitudinal analyses dewt K Population 1 2 amp 3 Longitudinal analyses involving 4 e WAVES 2 amp 3 or Waves 1 2 amp 3 dewts K Sample 1 2 amp 3 Longitudinal analyses involving te ere Waves 2 amp 3 or Waves 1 2 amp 3 K 1 2 amp 3 Longitudinal analyses involving Waves 2 amp 3 or Waves 1 2 amp 3 fweight K Population
46. as Example analysis SAS The following code gives the proportion of children eating or drinking while watching a TV video DVD or movie at any time of day for the B cohort at Wave 1 Statements 1 and 2 tell SAS to create a new dataset beginning with the data in the mtud diary2 file you will need to use your own library name The third statement tells SAS to treat the time use data as a multidimensional array x containing 96 rows of 40 columns each The next statement tells SAS to set up a new array of 96 variables Tveat into which the data for eating in front of the TV will be derived Statements 5 to 8 contain a do loop which runs across all 96 time periods Statement 5 tells SAS to create a variable i to keep track of which time period is being worked on and to give it the values 1 to 96 in turn Statement 6 tells SAS to allocate the value 100 at the position in the Tveat array for the current time period if the child was eating or drinking column 4 in the array and was watching a TV etc column 12 in Statement 7 says the value of O will be assigned if the child either wasn t eating or drinking or wasn t watching TV etc and the diarist wasn t unsure of the child s activities for the time period This means that cases where the diarist wasn t sure or didn t fill any information in for activities in this time period will have missing data Statement 8 finishes to do loop and statement 9 finishes the data ste
47. asked of or about which people at which wave The Topic ID field gives the topic and associated two digit question number for each item where this is appropriate It can be used to link derived items with their associated input items Please contact the LSAC Data Management team if you need any help with using the Data Dictionaries The data dictionary reflects the variables that are included in the main datasets ie lsacgrbO Isacgrb2 Isacgrb4 lsacgrb6 Isacgrk4 Isacgrk6 Isacgrk8 Isacgrk10 Items from the study child household and the PLE household modules the NAPLAN items and the Medicare items are not in the data dictionary LSAC Data User Guide November 2013 49 9 Data Transformations The data from many of the responses to questions have been transformed to assist data users 9 1 Transformations to ensure consistency LSAC contains a number of items that have been asked slightly differently in different waves Where this is logically supportable items are recoded to match the variables produced from other waves These recoded versions are provided in addition to the original item response Some examples of this are e Income is generally collected as a continuous variable however for the PLE in Wave 2 it was collected using five categories To assist users in comparing the responses of different informants an additional variable containing the continuous income information recoded into these five categories is ad
48. be consistent for each variable representing the same construct for a different subject informant or wave LSAC Data User Guide November 2013 43 For example the Parent 1 s rating of their own health quality at Wave 1 for the B cohort ahs13a has the variable label 0 1 P1 PIL D1 Global Health Measure 0 1 is the age indicator 1 is the informant subject indicator PIL D1 indicates the variable comes from the first question of Section D of the Parent 1 Leave Behind questionnaire Global Health Measures is the construct label total score for the Parent 1 parental warmth scale for the K cohort at Wave 2 dbwarm id 6 7 P2 Warm parenting 6 7 is the age indicator P2 is the informant indicator there is no questionnaire position as the variable is calculated from multiple questions Warm parenting is the construct label 7 10 Missing value conventions Missing data are coded as follows LSAC Data User Guide November 2013 Not applicable when explicitly available as an option in the questionnaire Don t know Refused or not answered Section refused Not asked due to one of the following reasons a question skipped due to answer to a preceding question e g if a child never repeated a grade the following question regarding what grade the child repeated was not asked skipped b a form was not returned or consent to participate was not given e g if a teacher form was not
49. bers R L amp Skinner C J Eds 2003 Analysis of Survey Data Chichester Wiley Cusack B amp Defina R 2013 Wave 5 Weighting and non response LSAC Technical Paper No 10 Australian Bureau of Statistics Canberra Daraganova G amp Sipthorp M 2011 Wave 4 Weights LSAC Technical Paper No 9 Australian Institute of Family Studies Melbourne Levy P S amp Lemeshow S 1999 Sampling of populations Methods and applications 3rd Edition New York Wiley Misson S amp Sipthorp M 2007 Wave 2 weighting and non response LSAC Technical Paper No 5 Australian Institute of Family Studies Melbourne National Childcare Accreditation Council 2003 OSHCQA Quality Practices Guide 1 Edition NCAC Sydney Australia National Childcare Accreditation Council 2003 QIAS Validation Report one Edition NCAC Sydney Australia National Childcare Accreditation Council 2004 FDCQA Quality Practices Guide 2 Edition NCAC Sydney Australia National Childcare Accreditation Council 2005 FDCQA Quality Practices Guide 3 Edition NCAC Sydney Australia National Childcare Accreditation Council 2006 QIAS Quality Practices Guide 1 Edition NCAC Sydney Australia Rowe K 2006 The measurement of composite variables from multiple indicators Applications in Quality Assurance and Accreditation Systems Childcare Background paper prepared for the National Childcare Accreditation Cen
50. ble a_a a a a a Wave 3 responding Wave 4 available 4929 96 5 4774 95 8 9703 96 2 Wave 4 responding 4241 183 0 860 4164 83 5 872 8405 833 866 Wave 5 available 4884 966 4735 95 0 9619 95 3 Wave 5 responding 4085 80 0 91 1 3956 794 835 8041 79 7 83 6 Between waves j j j j j Wave 1 5 sent h Wave 1 5 returned h Wave 2 5 returned 3268 635 640 3287 655 660 655 6 Wave 3 5 sent 472 9 4641 1931 9413 933 Wave 3 5 returned 3012 59 0 63 1 2972 59 6 640 5984 593 63 6 available sample excludes those who opted out of the study between waves Some additional families also opted out permanently during the fieldwork process those who had home visit Table 10 details the reasons why interviews were not obtained in Waves 2 3 4 and 5 Table 10 Response status and reasons for non response by wave Wave 2 Wave 3 Wave 4 Wave 5 Response status No No No No Responding 9070 91 1 8718 89 0 8405 86 6 8041 83 6 Away entire 61 0 6 93 1 0 135 1 4 88 0 9 enumeration period Death of study 5 0 1 1 0 01 0 0 1 0 01 child Total starting 9960 100 0 9800 100 0 9703 100 0 9619 100 0 sample LSAC Data User Guide November 2013 63 13 Important issues for data analysis The new Data Issues series has been initiated with a set of papers that had appeared as attachments
51. bout 35 of families who were sent the initial letter refused to take part in the study The main reasons given to interviewers for not participating in the study were not interested too busy 57 not capable moving overseas 9 husband refused 9 and illness death 8 The remaining 13 of families were not able to be contacted despite intensive efforts from interviewers Non response analysis was undertaken to determine how representative the sample is of all Australian children in the scope of this study and adjustments have been made to the survey weights to allow for this For further information on the weighting and non response see LSAC Technical paper 3 Wave 1 weighting and non response analysis www aifs gov au growingup pubs technical index html LSAC Data User Guide November 2013 62 Response in later waves Table 9 summarises the response from families in later waves using the Wave 1 sample and available sample as the bases for comparisons Table 9 Sample size and response rate for each wave and cohort of LSAC B cohort K cohort Total Resp Resp rate Resp esp jResp rate of rate of ore of Noo available available No available i Wave 1 i iWave i i i i d d sample isample sample 1090 Main waves ce Wave 1 original Wave 2 responding 4606 90 2 1912 4464 89 6 909 907 h Wave 3 availa
52. cccccccecccseececesecscsescscsescecscscsessseeseceseseeees 50 93 SUMMARY MEASURES FOR SCALES ccccsscesssecsceescececseceeseecscceeseecssecessecesssecessecssscessevenseeneees 50 94 OUTCOME INDEX MEASURES c cceecceessecssecescecessccecscecessceeseecesscessecesssceessecesseecssecesseeessensseeeesees 51 10 CONFIDENTIAL ISA TION 52 10 1 IN2CONFIDENGE DATA tnde extera eh Recte ST ES YER RECEN ON 52 10 2 GENERAL RELEASE DATA eec ceret ere eod ee E e gena Ee E eu eve evene ue ee y eee X EC Y e eee Pee ey ene 52 11 DATA TIMPUTA TION sisssececcesseseesessesesvetvssssevtbesvesetsesvesessestetstvesssat daceesedsedeestesestodudvesesesbuestssiuese 53 12 SURVEY METHODOLOGY 55 TZT SAMPLE DESIGN E Oe Pe Y EINER ec Pc b e n 55 12 2 DEVELOPMENT AND TESTING OF SURVEY INSTRUMENTS ccccccccccccccccccseesececesececeseceseseeeseseeees 56 12 3 DATA COLLECTION teeta EE e 57 12 4 FIELDWORK esses stesse 62 13 IMPORTANT ISSUES FOR DATA ANALYSIS creen eee eee enne seen oeste tone ee eese eaae eee 64 13 1 WEIGHTING AND EXTERNAL VALIDITY eene eee nennen sess es sese eese esses sse eset essen 64 13 2 UNIT OE ANALYSIS eee tn e ee bees o ote e bes 71 13 3 GE ATINT
53. dard Classification of Occupations ASGC Australian Standard Geographic Classification ATSI Aboriginal and Torres Strait Islander BMI Body Mass Index CA Carer Allowance CAI Computer Assisted Interview Computer Assisted Personal Interview CATI Computer Assisted Telephone Interview CBC Centre Based Carer CCB Child Care Benefit CSR Child Self Report DFRDB Defence Forces Retirement and Death Benefits Scheme DSP Disability Support Pension DSS Department of Social Services DVA Australian Government Department of Veterans Affairs F2F Parent 1 Face to Face Interview FCF Family Contact Form FDC Family Day Care FDCQA Family Day Care Quality Assurance FTB Family Tax Benefit FTBA Family Tax Benefit A FTBB Family Tax Benefit B GPS Global Positioning System HBC Home Based Carer IVF In Vitro Fertilisation LDC Long Day Care LOTE Language Other Than English LSAC Data User Guide November 2013 LSAC Longitudinal Study of Australian Children MBS Medicare Benefit Scheme MSN Medicare Safety Net MR Matrix Reasoning test NCAC National Childcare Accreditation Council NILF Not In the Labour Force NSA Newstart Allowance OMR Optical Mark Recognition OSHCQA Outside School Hours Care Quality Accreditation P1D Parent 1 During Interview Questionnaire PIL Parent 1 Leave Behind Questionnaire P1SC Parent 1 Self Complete Questionnaire P2
54. ded wherever income has been collected continuously e In Wave 1 respondents were asked if the child received any regular childcare from a grandparent In Wave 2 respondents were given the option of this being a maternal or paternal grandparent In addition to the two variables giving this information separately for maternal and paternal grandparents an extra variable has been added for whether the child is being cared for by a grandparent 9 Transformations to update information From Wave 2 on there are a number of places in the questionnaire where respondents are asked about something happening since the last interview or in the last 2 years if the study child is living in a new household For example in Wave 1 Parent 1 was asked how many homes the study child had lived in since birth while in subsequent waves Parent 1 was asked how many homes the study child had lived in since the last interview The datasets for the subsequent waves contain variables on the number of homes since the last interview and a tally of all the home the study child has ever lived in 93 Summary measures for scales The appropriate summary measure for each scale is included based on advice from the Consortium Advisory Group Where it is possible to logically implement either a mean or a sum score for a psychological scale or subscale the preference of the Consortium Advisory Group was to provide the calculation of means except in cases where convention wo
55. e ages of 0 and 7 years should use the 4 item version and for analysts comparing hostility between the ages 0 to 9 years should use the 3 item version 9 4 Outcome Index measures A unique component of the derivation and analysis work was the development and derivation of the LSAC Outcome Index a composite measure that indicates how children are developing LSAC tracks the development of children across multiple domains and the Outcome Index provides a means of summarising this complex information for policy makers the media and the general public as well as data users In contrast to some other indices which focus on problems or negative outcomes the LSAC Outcome Index wherever possible incorporates both positive and negative outcomes reflecting the fact that most children have good developmental outcomes Thus the Outcome Index has the ability to distinguish groups of children developing poorly from those developing satisfactorily The rationale and methodology used to develop the Outcome Index are described in the LSAC Technical Paper No 2 Summarising children s wellbeing the LSAC Outcome Index Papers on the derivation of the Waves 2 and 3 Outcome Index are forthcoming Any users planning to use the Outcome Index are strongly advised to read the technical papers as they contain important information about the correct use of the variable www aifs gov au growingup pubs technical index html From Wave 4 the Outcome Index is not c
56. e factors were incorporated into the Wave 1 survey weighting so that to the best extent possible the use of the sample weights offset the bias that may be introduced into the data due to differential non response patterns At each subsequent wave of data collection weights have been adjusted to account for the differential probability of response as estimated by regression The weights are then calibrated back to the stratum benchmarks and a small number of cases have their weights top or bottom coded to prevent any case having too great or small an effect on the data From Wave 3 onwards it is required to produce longitudinal as well as cross sectional weights for the first time Cross sectional weights adjust the sample attained at current wave to be representative of the population at the time of selection while longitudinal weights do the same for the sample that has responded to all waves of the survey More detailed information on the weighting variables can be found in LSAC Technical Papers no 3 5 6 9 and 10 www aifs gov au growingup pubs technical index html Three types of weight are included in the LSAC datasets Child population weights these weights are used to produce population estimates based on the LSAC data e g based on LSAC data there are 22 464 children born in March 2003 to February 2004 in Australia that were never breastfed LSAC Data User Guide November 2013 65 The sum of the responding cohor
57. e first 2 periods and children born in September February in the later fieldwork periods 84 of the interviews were conducted prior to September 2006 Figure 6 shows the distribution of interviews over time for Wave 2 fieldwork Fieldwork started later than in Wave 1 due to the additional work required to prepare the CAI instrument Wave 3 Fieldwork was organised as per Wave 2 The green line in Figure 6 shows the distribution of interviews over time for Wave 3 fieldwork Wave 4 Fieldwork was organised as per Waves 2 and 3 The dark blue line in Figure 6 shows the distribution of interviews over time for Wave 4 fieldwork However as the children are getting older the age differences within a cohort are less significant and to assist the efficiency of work allocations to Interviewers in Wave 4 not as much emphasis was given to following interviews within the set phases Wave 5 Fieldwork was organised as per Waves 2 3 and 4 Figure 6 shows that the distribution of interviews for Wave 5 fieldwork was more spread out across the months than for previous Waves Figure 6 Month of interview for study families in Waves 1 to 5 2500 2000 lews 1500 1000 500 Number of interv Month Wavel1 9 Wave2 tWave3 Bi Wave4 Wave 5 LSAC Data User Guide November 2013 59 12 3 4 Contact process Wave 1 For most families the interviewer only had the name and address of the Medicare cardh
58. e previous wave unless it was confirmed that the address was out of date Interviewers then followed up with a telephone call to make an appointment for an interview If the contact information was out of date the interviewers tried to contact secondary contacts of Parent 1 these details were given by Parent 1 in Wave 1 and are updated each wave to locate the family One visit to the address was also made If the family could not be located the interviewer referred this back to the office for tracking After an appointment for interview was made the interviewer confirmed the appointment the day before the appointment 12 3 5 Foreign language interviews Wave 1 As part of the Medicare Australia mail out a brochure was included with information about the study in nine languages Medicare Australia staff made use of the Telephone Interpreter Service TIS to assist with calls where required Apart from this brochure no other study material was or has been translated into other languages and instead interpreters were used An interpreter was required in 3 of interviews with over 50 languages involved In most cases 138 a member of the family or friend was preferred as the interpreter In 76 cases an I view employee was able to act as interpreter and in 96 cases an interpreter was employed LSAC Data User Guide November 2013 60 Wave 2 A total of 110 interviews 1 were conducted in a language other than English in 23 dif
59. e same Quality Areas but have had the number of principles used to assess these areas reduced from 35 to 30 The old scheme has 10 Quality Areas assessed by 35 principles while the new has 7 Quality Areas assessed by 30 principles For LDC all Wave 1 centres were assessed under the 5 Validation Report gnd Edition NCAC 2003 From July 2006 accreditation decisions were made under the QIAS Quality Practices Guide 1 Edition As a consequence some of the Wave 2 and 3 accreditations were made under the new scheme while some were made under the old scheme Before and after school care arrangements are assessed in the guidelines laid out in the OSHCQA Quality Practices Guide 1 Edition 2003 In Wave 2 and 3 accreditations were made under the new scheme while some were made under the old scheme The variables included are Date of accreditation Date of validation Accreditation status LDC v1 Quality area 1 Relationships with Children LDC v1 Quality area 2 Respect for Children LDC v1 Quality area 3 Partnerships with Families LDC v1 Quality area 4 Staff Interactions LDC v1 Quality area 5 Planning and Evaluation LDC v1 Quality area 6 Learning and Development LDC v1 Quality area 7 Protective Care LDC v1 Quality area 8 Health LDC v1 Quality area 9 Safety LDC v1 Quality area 10 Managing to Support Quality LSAC Data User Guide November 2013 23 LDC v2 Quality area 1 Staff relatio
60. ecords to create derived items from the Medicare datasets The following code samples create a variable ben07 for the amount of PBS benefits paid for a child in 2007 Note that this variable will initially be missing for cases that had no PBS claims in 2007 as well as those for which data linkage was unsuccessful The match file can be used to distinguish between these cases and set ben07 to O for those with no claims This file contains a variable called medicare which is 1 if linkage is successful for a case and 0 otherwise SAS proc means data m pbs nway sum class hicid var benefit where datesupp gt mdy 1 1 2007 and datesupp lt mdy 1 1 2008 output out temp sum ben07 run data temp merge temp m3 match by hicid if medicare 1 and ben07 then ben07 0 run LSAC Data User Guide November 2013 29 SPSS temp select if datesupp gt date dmy 1 1 2007 amp datesupp lt date dmy 31 12 2007 aggregate outfile temp sav break hicid ben07 sum benefit get file temp sav match files file file match sav by hicid if medicare 1 amp missing ben07 07 0 execute STATA note that the collapse command will delete all other data than hicid and ben07 make sure to save it to a new file collapse sum ben07 benefit if datesupp gt mdy 1 1 2007 amp datesupp lt mdy 1 1 2008 by hicid merge hicid using match replace ben07 0 if medicare 1 amp ben07 keep
61. ers 4 through to whatever is required Each household member retains the same member number throughout the study even if they leave and re enter the Study Child s home Due to the requirements of the CAI instrument some families have gaps in member numbering for example where someone is Member 5 but Member 4 has never been assigned Member 1 is denoted by m1 in the above convention Member 2 as m2 and so on as required As families change from Wave 2 on Parent 1 Parent 2 Mother or Father can have any member number apart from 1 For this reason an extra set of variables has been derived to give the details for the Parent 1 Parent 2 Mother and Father at any age This subscript is an age indicator and then either pl p2 or A set of indicator variables tracks the household member number of Parent 1 Parent 2 Mother and Father at each wave For example bp2mn tells you the household member number of Parent 2 when the child is aged 2 3 while cmmn gives the member number of the mother when the child is aged 4 5 Some examples zf02ml the gender of the study child z unchanging characteristic f Family 02 gender m1 Study child LSAC Data User Guide November 2013 38 e bfOlm2 whether the Wave 1 Parent 1 is present in the household when the child is aged 2 3 b child aged 2 3 f Family 01 present for wave m2 Wave 1 Parent 1 cf01m3 whether the Wave 1 Parent 2 is
62. ferent languages Family or friends assisted in 58 cases ABS interpreters helped in 37 cases and a TIS interviewer was used for 15 families An interpreter was arranged whenever requested or judged necessary by the interviewer The reduction in use of interpreters between waves is presumably due to the increased confidence in English that has been gained by respondents in this time Wave 3 A total of 97 interviews needed an interpreter in 24 languages Family or friends assisted in 58 cases ABS interpreters helped in 31 cases and a TIS interviewer was used for 8 families Wave 4 A total of 93 interviews needed an interpreter in 26 languages Family or friends assisted in 50 cases ABS interpreters helped in 29 cases and a TIS interviewer was used for 14 families Wave 5 A total of 81 interviews needed an interpreter in 18 languages Family or friends assisted in 47 cases ABS interpreters helped in 24 cases and a TIS interviewer was used for 10 families 12 3 6 Indigenous communities Although the sample selection process excluded 40 of areas classified as remote by the ABS areas that typically have a high Indigenous population there were still a number of postcodes selected that contained some remote Indigenous communities hence strategies have been put in place to enumerate these communities Where feasible communities were visited or telephoned and personal contact made with a number of community organisations from whom as
63. he file represents an immunisation that the child has had e MBS Each record on this file represents a benefit claim e PBS Each record represents a benefit claim LSAC Data User Guide November 2013 27 7 2 10 1 ACIR file Records are currently available for payments received from birth to early 2013 The following variables are included on the file Child identification number Vaccination code Vaccination name Scrambled provider ID Date of receipt of payment Date of immunisation Some of the vaccination codes contain dose numbers which indicate where a vaccine has been received in a series of doses The sequence of doses for these has been included in the dataset i e 1 2 etc If a dose is missing it means that it was either not reported to ACIR or it was missed 7 2 10 2 MBS file Records are currently available for services between January 2002 or birth for the B cohort and early 2013 The following variables are included on this file Child identification number Item number Item name Amount of benefit paid Hospital indicator Scrambled provider Date of payment Date of service Some cases have very small or negative benefit amounts In relation to negative benefits this indicates that an adjustment has been made to the Medicare benefit records There are several reasons why this may happen sometimes this is a correction of a data entry made against the wrong individual reference number on a Medica
64. here the Pl K and B child interview are covered in detail apart from what was done on Day 1 New Interviewers were teamed with an experienced Interviewer allowing for mentoring throughout the training course and for the new Interviewers to be the Interviewer during practice sessions 12 3 3 Fieldwork periods Wave 1 Selected postcodes were divided into 2 groups for maximum field efficiency The target population was also divided into 2 groups children born March August older in one group and children born September February younger in the other The fieldwork was divided into 4 phases e Phase 1 started in mid March 2004 for the older children in the first group of postcodes e Phase 2 started at the end of April for the older children in the second group of postcodes e Phase 3 started in June for the younger children in the first group of postcodes and e Phase 4 started in late July for the younger children in the second group of postcodes Follow up continued throughout 2004 The blue line in Figure 6 shows the distribution of interviews over time for Wave fieldwork Wave 2 Again there were broadly 4 fieldwork periods although the dates for these varied from state to state Regional offices of the ABS were able to organise the work to suit LSAC Data User Guide November 2013 58 the availability of interviewers and other work As far as possible ABS tried to interview the children born in March August in th
65. hers known as the LSAC Consortium Advisory Group The Wave 1 data collection was undertaken for the Institute by Colmar Brunton Social Research and I view NCS Pearson private social research companies Data collection for Waves 2 3 4 and 5 was undertaken by the Australian Bureau of Statistics 4 3 Timelines Development work for the study commenced in March 2002 with the testing phase continuing through 2003 involving over 500 families Recruitment to the study of over 10 000 children and their families took place from March until November 2004 From 2004 the families have been interviewed every two years In addition between waves mail out questionnaires were also sent to families in 2005 2007 and 2009 Sample design The focus of the study is on the developmental pathways of Australian children Therefore the child is the sampling unit of interest A dual cohort cross sequential design was employed as shown below Cohort Wave 1 Wave 2 Wave 3 Wave 4 Wave 5 B cohort 0 1 sa Ligen ep ccs years LSAC Data User Guide November 2013 8 K cohort 4 5 years 6 7 years 8 9 years 10 11 years 12 13 years The two cohorts of children were selected from children born in a 12 month period B cohort infant cohort children born March 2003 February 2004 Kcohort child cohort children born March 1999 February 2000 Further information about the design of the sample is available
66. hild was home schooled Linkage for of NAPLAN data for children whose consent was received at Wave 4 15 scheduled to be released in April 2012 The Wave 4 LSAC NAPLAN release includes K cohort NAPLAN results for years 2008 and 2009 The update of the LSAC NAPLAN file with NAPLAN results for years 2010 and 2011 is scheduled for April 2012 Starting from 2013 the LSAC NAPLAN file will be updated with new NAPLAN results every two years and released along with the main wave release In Wave 5 LSAC NAPLAN release includes B amp K cohort NAPLAN results for 2008 to 2012 LSAC Technical Paper 8 includes a detailed discussion of data compendium and data issues that should be considered when using the LSAC data The report is available from www aifs gov au growingup pubs technical index html 7 2 13 Wave 2 5 data The data from the Wave 2 5 mail out is included in two separate datasets Unlike Wave 1 5 in relation to Wave 1 families that responded to Wave 2 5 did not necessarily respond to Wave 2 Merging these with the Wave 2 datasets would have resulted in a number of largely blank cases on the data file The data in the Wave 2 5 file consists of questionnaire items a small number of derived items and linked census data based on postcode of responding families at the time of Wave 2 5 Unfortunately formatting of the questionnaires resulted in some respondents skipping items they should have answered Imputation has been performed o
67. if 07 sort hicid save temp replace 7 2 11 Household composition data At each wave of data collection responding families are asked to give the details of the people currently residing in their household as well as people who have come and gone between waves but lived with the study child for at least three months This dataset contains one record for each study child detailing the composition of their household since their recruitment to the study up to the most recent data collection Details collected about the study child Parent 1 and Parent 2 are included in each main dataset along with a number of derived variables on household composition LSAC Data User Guide November 2013 30 7 2 12 LSAC NAPLAN data In Wave 3 81 of parents of K cohort children gave consent for their child s data to be linked with NAPLAN data for the duration of the study Linkage was successful for 96 of children For 4 of children the NAPLAN data were not found either because these children had not sat NAPLAN tests yet or they sat the NAPLAN tests in 2008 or 2009 but a match was not found Families who did not give consent or who did not participated at Wave 3 were asked again at Wave 4 Out of 964 families who were followed up in Wave 4 847 gave consent to link NAPLAN results In Wave 4 95 5 of parents of B cohort children gave consent to link NAPLAN AEDI results This percentage excludes 9 B cohort families where the study c
68. in the sample with proportions 10 per cent higher than in the 2001 Census LSAC Data User Guide November 2013 76 Other differences include e children in lone parent families are under represented e children with two or more siblings are under represented and only children are over represented in the infant cohort particularly for the B cohort at Wave 1 e children from an ATSI background although not for the B cohort at Wave 1 e children with mothers who speak a language other than English at home are underrepresented and e children in New South Wales are under represented Table 13 shows the number of children in the Wave 1 sample with selected characteristics and gives the Waves 2 3 and 4 response rates for children with these characteristics As can be seen in the table the greatest sample loss has been from Indigenous families and families where Parent speaks a language other than English at home Table 13 Response rates at Waves 2 3 4 amp 5 by selected sample characteristics Wave 1 N responding responding responding responding to Wave 2 to Wave 3 to Wave 4 to Wave 5 Characteristics B K B K B K B K B K Fullsample 5107 4983 902 896 859 869 831 836 800 794 Study child 2610 2537 90 0 89 8 86 3 87 2 838 840 80 3 79 5 male Study child 2497 2446 904 89 4 85 5 866 823 83 2 79 7 79 1 Vou ERE ECCE CONES Study child 230 187 78 3 81 8 648 663 630 513 600 59 9 Indigenous Mother speaks 740 778 83 9 83 8 75
69. ink type variable is included to tell data users whether the linkage was performed using SLA or postcode and whether the 2001 census 2006 census 2011 census or all were used 7 1 2 National Childcare Accreditation Council data A key research question in LSAC relates to the impact of child care on children s developmental outcomes over time While LSAC collected parent report information on children s child care histories and carer reports on the child care environment relatively little systematic information was collected on quality of child care The National Childcare Accreditation Council Inc NCAC has quality assurance data on every Long Day Care LDC centre some Family Day Care FDC schemes and some Before and After School Care providers The LSAC dataset includes linked NCAC data for most children using LDC or FDC at Wave 1 where contact details of this care were obtained and matched with NCAC data The match rate obtained during the linkage process was 78 for Wave 1 82 for Wave 2 84 for Wave 3 and 92 for Wave 4 One complication in using the NCAC data is due to the change of accreditation systems for both FDC and LDC In Wave 1 all cases had FDC assessed under the guidelines laid out in 2 edition of the FDCQA Quality Practices Guide NCAC 2004 while from Wave 2 and onwards all cases have been assessed under the 3 edition of this reference which was introduced in July 2005 The revised guidelines contain th
70. interviewer would be in their area I view maintained a 1800 number for families selected in the study which was transferred to the Australian Bureau of Statistics ABS once ABS had responsibility for the data collection from Wave 2 on 12 2 Development and testing of survey instruments 12 2 1 Pretesting Pre testing of new material and processes is undertaken at each wave of the study comprising small scale pre tests and cognitive interviews In Waves 1 and 2 more formal piloting was also undertaken Small scale testing is also undertaken for the between wave surveys Wave I e Development began in March 2002 e Small scale pre testing occurred in September October 2002 e Pilot test with about 50 families from each cohort was conducted in March April 2003 Wave 2 e Development began in July 2004 e Small scale pre testing occurred in September October 2004 e Pilot test with 86 families conducted in April 2005 Wave 3 e Development began in March 2006 e Pretesting occurred in a number of stages from mid 2006 to March 2007 e No pilot test was required Wave 4 e Development began in February 2008 e Pretesting occurred in a number of stages from mid August 2008 to June 2009 No pilot test was required Wave 5 e Development began in February 2010 Pretesting occurred in a number of stages from mid June 2009 to March 2010 pilot test was required 12 2 2 Dress Rehearsal In Wave 1 a Dress Rehearsal
71. isfies the parental requirements i e PLEs who see the Study Child at least once a year 2 PLE s contact details are available 3 Parent 1 did not explicitly refuse to contact the PLE LSAC Data User Guide November 2013 19 6 The LSAC data release Data users are required to read the manual for the access to and use of DSS longitudinal survey datasets complete a dataset application form and sign a deed of license Users must abide by strict security and confidentiality protocols Instructions on how to access data can be found on the LSAC website http www aifs gov au growingup data index html 6 1 1 Data security requirements The deed of licence stipulates numerous security requirements for the data including e The LSAC CD ROM MUST be kept secure in a locked filing cabinet or other secure container when not in use e The LSAC data and any derivatives of the LSAC data MUST be stored on a password protected computer or network e Your password MUST include a mixture of upper and lowercase characters be at least 8 characters long and include some non alphanumeric characters such as etc e Any printed unit record output MUST be stored in a locked filing cabinet or other secure container when not in use Any printed unit record output MUST be shredded if no longer required You MUST NOT provide the unit record data to any unauthorised individual e There MUST be a means of limiting access to the work area where
72. luding e study methodology introduction to the datasets issues for data analysts e g weighting clustering confidentialisation variable naming user resources eg data dictionary labeled questionnaires See the LSAC website for details on when training sessions are being offered 14 1 Online assistance An email alert list is used to convey key information and updates to users Important information distributed via the email alert list is also stored in the data access area of the Growing Up in Australia website This area contains all reference material made available to users in downloadable form Excel Data Dictionary critical updates and alerts as distributed through the email alert list updates on data user workshops 14 2 Getting more information More information on Growing Up in Australia and its progress can be found on the LSAC website http http www growingupinaustralia gov au index html Further enquiries can be directed to aifs Isac aifs gov au or by contacting LSAC Data Manager Australian Institute of Family Studies Level 20 485 La Trobe Street Melbourne VIC 3000 Tel 61 3 9214 7879 Fax 61 3 9214 7839 LSAC Data User Guide November 2013 78 15 References Baxter J 2007 Children s time use in the Longitudinal Study of Australian Children Data quality and analytical issues in the 4 year old cohort LSAC Technical Paper No 4 Australian Institute of Family Studies Melbourne Cham
73. n of the two cohorts at each Wave The figures show the age of the child as a base figure ie 0 2 4 6 or 8 years plus a number of months For example a B cohort child aged 3 years 1 month at time of interview in Wave 2 is shown against 13 on the x axis on the red line LSAC Data User Guide November 2013 71 Figure 8 Age distribution of B cohort sample at each wave B cohort Wave 1 0 years 7t B cohort Wave 2 2 years B cohort Wave 3 4 years B cohort Wave 4 6 years Wave 5 8 years 7 7 K cohort Wave 1 4 years 7i K cohort Wave 2 6 years K cohort Wave 3 8 years K cohort Wave 4 10 years K cohort Wave 5 12 years 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Months above base age LSAC Data User Guide November 2013 72 13 4 Time between interviews Effort is made to ensure that the time between interviews is close to two years however in some cases this is not possible Figure 10 shows the distribution of the intervals between waves Figure 10 Distribution of time between interviews B Cohort Wave 1 to 5 35 4 X8 cohort Wave 1 2 G 8 cohort Wave 2 3 30 Ww9B cohort Wave 3 4 ee g8 cohort Wave 4 5 25 Percentage m 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 Number of Months between interviews K Cohort Wave 1 to 5 30 T a K cohort
74. n some items where it was possible to infer the data for these questions based on responses to other questions See the Data Issues paper for further information 7 2 14 Wave 3 5 data The data from the Wave 3 5 mail out is included in a separate dataset in the same way that data from Wave 2 5 was included The data in the Wave 3 5 file consists of questionnaire items a small number of derived items and linked census data based on the postcode of responding families at the time of Wave 3 5 Imputation has been performed on some items where it was LSAC Data User Guide November 2013 3 possible to infer the data for these questions based on responses to other questions See the Data Issues paper W3 5 for further information 7 2 15 ACARA MySchool Data Data has been obtained from ACARA ACARA is responsible for collating NAPLAN data received from Australian schools collecting school characteristics and managing the MySchool Web site Some of the data ACARA collects and collates on Australian schools is publically available on the MySchool website School data about the schools LSAC participants attend has been linked onto the LSAC survey datasets and is available to data users LSAC Data User Guide November 2013 32 Variable naming conventions The variable naming convention was developed so that variables have predictable names across waves and informants and so that thematically linked variables have similar names wherever
75. n with the input variables they come from question id i e variable name without age or subject informant useful for sorting position in file order file wave cohort position of question in questionnaires person label child s age variable label briefly describing each data item topic construct measure question as found in the survey instruments response categories population with data SAS format notes field indicating other information users should know about the data item 8 3 1 Excel Data Dictionary The Excel data dictionary contains two spreadsheets one with the complete detailed listing of variable attributes another with a shorter listing in a print ready format The print ready format contains the variable name question responses and population fields however it is not a difficult task for users to make their own printable versions if they prefer other fields The Excel version can be easily filtered using the drop down menus in the first row of the spreadsheet For example to find all the items on teacher practices in the lsacgr6 file K cohort at Wave 2 first click on the drop down menu in the File field as shown in Figure 5 and select B2 Next repeat the process for the Topic field selecting Teaching practices After the search is finished all variables can be displayed by either clicking the show all option in each of the fields that have been filtered see Figure 5
76. nal educational educational childcare childcare yt tilled urna ERIS program program program program b 2nd oe Before Before Before SE childcare childcare childcare school care school care school i 3 3H a After After After pone childcare childcare childcare school care school care school care Other 3 ae childcare childcare ba ore alle Oe etek tl esses ostio hace e cea Umes re Program Program Program child child child would would would E attend if attend if attend if attending attending attending ff School school school X Any Any extra Any extra Any extra All items that form a scale have a single question number Where applicable the name of the item also indicates the relevant subscale or sub subscale please note that this is done only where it is possible to do so due to the eight character limit for the name of an item An example of how this is applied is shown with the Conduct Problems and Peer Problems subscales of the Strengths and Difficulties Questionnaire see Table 6 These are subscales that both Parent 1 and the teacher filled out in Waves 1 and 2 for the K cohort LSAC Data User Guide November 2013 36 As shown e The 6 character in the variable name in this case represents an informant indicator a is for Parent 1 t
77. name or the age indicator is z then this part of the variable label will not be included E g label zf04m1 SC DOB here no age is associated with the variable because it doesn t change with time hence no age indicator is included label df03m1 6 7 SC Age this variable is a variable that changes over time so the age indicator is required in order to establish when the question was answered Informant subject gives the informant or subject of the question as contained in the variable name For household composition variables involving Parent 1 Parent 2 Mother or Father the age of the study child at which the person s status as parent 15 determined will also be indicated e g M 0 1 is the Mother when the child is aged 0 1 years old If the information only exists for one subject or informant in the study this part of the variable label will not be included Questionnaire position indicates the location of the question the data was obtained from within the LSAC questionnaires e g F2F H2 is question H2 of the Face to Face Interview This part of the variable label is left blank for derived items such as scales and other non input items but included for Mother Father variables where the location of both the P1 and the P2 variables are given Construct label provides a description of what information is actually contained in the variable e g Sex Birthweight This part of the variable name will
78. ndal C E amp Sautory O 1993 Generalised raking procedures in survey sampling Journal of the American Statistical Association 88 1013 1020 Kalton G 1983 Compensating for missing survey data Research report series Institute for Social Research University of Michigan Lepkowski J M 1989 Treatment of wave nonresponse in panel surveys In D Kasprzyk G Duncan G Kalton amp M P Singh Eds Panel Surveys 348 374 New York Wiley Levy P S amp Lemeshow S 1999 Sampling of populations Methods and applications 3rd ed New York Wiley Pfeffermann D Skinner C Holmes D J Goldstein H amp Rasbash J 1998 Weighting for unequal selection probabilities in multilevel models Journal of the Royal Statistical Society Series B 60 23 40 Skinner C J amp Holmes D J 2003 Random effects models for longitudinal survey data In R L Chambers amp C J Skinner Eds Analysis of Survey Data 205 218 Chichester Wiley Tabachnick B G amp Fidell L S 1989 Using Multivariate Statistics 2nd ed New York Harper and Row Wolter K 1984 Introduction to Variance Estimation New York Springer Wright B D amp Masters G N 1982 Rating scale analysis Chicago MESA Press Information on related studies Fergusson D M Horwood L J Shannon F T amp Lawton J M 1989 The Christchurch Child Development Study A review of epidemiological findi
79. ng documentation is also useful to data users and is available on the study website http www growingupinaustralia gov au index html e Questionnaires and interview specifications marked with variable names including mock questionnaires for Computer Assisted Interview CAI instruments e Data Dictionary e Technical Papers on weighting non response and other issues e Data issues papers Feedback from data users suggests that browsing the marked questionnaires and interview specifications is often the best way to understand the breadth of information available in the study and find sections relevant to the proposed research topic Please read the Important issues for data analysis section carefully This section outlines aspects of the sample design that have important implications for interpreting analyses from the study Other information relevant to data users is contained in the Data users information pages on the website We welcome any feedback you have about this Data User Guide If there is something that you expected to find in the manual and didn t or if you had difficulty understanding any section please let us know by emailing aifs lsac aifs gov au LSAC Data User Guide November 2013 7 4 What is LSAC Growing Up in Australia the Longitudinal Study of Australian Children LSAC aims to examine the impact of Australia s unique social and cultural environment on the next generation The study will fu
80. ngs Pediatric and Perinatal Epidemiology 3 278 303 Freidin S Watson N amp Wooden M 2002 HILDA Survey Coding Framework Confidentialised Data HILDA project technical paper series The Melbourne Institute of Applied Economic and Social Research University of Melbourne Frick J R amp Haisken DeNew J P 2001 Structuring the HILDA Panel Considerations and Suggestions HILDA project discussion paper series The Melbourne Institute of Applied Economic and Social Research University of Melbourne Henstridge J 2001 The Household Income and Labour Dynamics in Australia HILDA Survey Weighting and Imputation HILDA project discussion paper series LSAC Data User Guide November 2013 80 The Melbourne Institute of Applied Economic and Social Research University of Melbourne National Longitudinal Survey of Children and Youth NLSCY 1999 Overview of survey instruments for 1998 99 data collection cycle 3 Catalogue no 89FOO78XPE no 3 Canada Statistics Canada Watson N amp Fry T R L 2002 The Household Income and Labour Dynamics in Australia HILDA Survey Wave 1 Weighting HILDA project technical paper series The Melbourne Institute of Applied Economic and Social Research University of Melbourne Watson N amp Wooden M 2002 The Household Income and Labour Dynamics in Australia HILDA Survey Wave 1 Survey Methodology HILDA project technical paper series The Melbourne Institu
81. nly information from the FCF available in the publicly released dataset being the information on LSAC Data User Guide November 2013 12 the family s home and neighbourhood In subsequent waves this information was included as part of the Interviewer Observations of the Face to Face Interview e Between Waves Questionnaires Wave 1 5 Wave 2 5 and Wave 3 5 are brief questionnaires sent to respondents to complete and return in the year between main waves of data collection Between wave surveys enable maintaining contact with study families and collecting information about activities and development in the year between the main waves 5 1 Child assessments 5 1 1 Physical measurements 5 111 For the B cohort in Wave 1 the child s weight was obtained by calculating the difference between the weight of Parent 1 or another adult with the child and the weight of the parent other adult on their own For the B cohort at all subsequent waves and the K cohort at all waves the child s weight was measured directly In Wave 1 the scales used were Salter Australia glass bathroom scale 150kgsX50gms In Waves 2 and 3 these scales were used along with HoMedics digital BMI bathroom scales 180kgsX100gms In Waves 4 and 5 Tanita Body Fat scales were used 5 1 1 2 Height Height is measured for children aged 2 years and older In Waves 1 2 and 3 height was measured using an Invicta stadiometer from Modern Teaching Aids In
82. nships with Children and Peers LDC v2 Quality area 2 Partnerships with Families LDC v2 Quality area 3 Programming and Evaluation LDC v2 Quality area 4 Children s Experiences and Learning LDC v2 Quality area 5 Protective Care and Safety LDC v2 Quality area 6 Health Nutrition and Wellbeing LDC v2 Quality area 7 Managing to Support Quality FDC Quality area 1 Interactions FDC Quality area 2 Physical Environment FDC Quality area 3 Children s Experiences Learning and Development FDC Quality area 4 Health Hygiene Nutrition Safety and Wellbeing FDC Quality area 5 Carers and Coordination Unit Staff FDC Quality area 6 Management and Administration OHS Quality area 1 Respect for Children OHS Quality area 2 Staff Interactions and Relationships with Children OHS Quality area 3 Partnerships with Families and Community Links OHS Quality area 4 Programming and Evaluation OHS Quality area 5 Play and Development OHS Quality area 6 Health Nutrition and Wellbeing OHS Quality area 7 Protective Care and Safety OHS Quality area 8 Managing to Support Quality Demographic data The data used to develop the quality areas was collected from six sources A self study report prepared by centre management A validation survey completed by the director A validation survey completed by staff A validation survey completed by families A validation report completed by an independent peer and A set of moderation ratings completed by
83. nt 5 8 Child and what fieldwork phase see Methodology section for more detail the child was selected to be part of in Wave 1 Phase 1 1 and 5 Phase 2 2 and 6 etc The second is the state the child was selected from 1 NSW 2 Vic etc The third indicates the part of state the child was selected from 1 2 capital city 3 4 rest of state The remaining 5 digits are a random number allocated by Medicare Australia Note that the stratum for selection may differ from the location of the child at interview and that the fieldwork phase may change from wave to wave 7 8 Indicator variables There are indicator variables in the main data files that indicate which parts of interview were incomplete These variables were created to flag to data users through yes no values that no data or only partial data exists for an instrument for example the CAST an informant for example parent 1 The data may be incomplete due a number of different reasons There may be no data if a self complete form was not returned parent child did not provide consent to obtain provide the data one of the informants refused to participate or when the interview was partially completed For example on the day of the interview the parent may consent to the child participating but refuse to participate themselves In this example there would be data for the sections where the study child is the informant however there would be no LSAC Dat
84. nts in each of two selected age cohorts e children born March 2003 February 2004 B cohort e children born March 1999 February 2000 K cohort 12 1 1 Sample selection and recruitment The sample was selected from Medicare Australia s enrolment database Within the selected postcodes the population was ordered by date of birth and then a random start and skip applied to select the children The actual number of children selected depended on which stratum the postcode was in but for most postcodes the aim was to recruit about 20 children per cohort per postcode The selection of children and corresponding Wave 1 fieldwork occurred in 4 phases partly to reduce the age range of children at interview and partly because some of the target population had not been born at the time of the first phase selection LSAC Data User Guide November 2013 55 Families of 18 800 selected children received letters of invitation to take part in the study sent by Medicare Australia Families could opt out of the study by phoning a 1800 number or returning a reply paid slip Medicare Australia 1800 staff were given training about the study and were able to answer queries and make note of other information for example telephone numbers After a 4 week opt out period Medicare Australia gave the contact names and addresses of remaining families to I view the Wave 1 data collection agency I view then sent another letter to families saying when an
85. older and which cohort the child was in In a small number of cases families who were keen to participate had contacted the 1800 numbers and supplied phone numbers and or best times to call Interviewers were required to make up to 6 visits to the address at different times of the day and on different days of the week A major challenge was that 7 of addresses were post office box addresses and although families with these addresses were specifically requested to make contact with the 1800 number to supply a residential address only a small proportion did so In addition many of the residential addresses held by Medicare were found to be out of date by the time the interviewers visited Interviewers made significant attempts to locate families for whom they did not have a current residential address by referencing White Pages and electoral rolls and speaking with neighbours and other local contacts Between waves Contact is maintained with study families between waves by sending birthday cards annual calendars and newsletters and via the between wave mail out questionnaires in Waves 1 2 and 3 These processes have resulted in some families contacting the ABS to update their contact information which helps when trying to arrange appointments for the main waves of interviewing Subsequent waves Pre interview letters plus a brochure outlining the processes for that wave were sent to all families who had not opted out of the study since th
86. ongitudinal analyses involving 5 Waves 2 3 4 amp 5 Waves 1 2 3 4 amp 5 13 1 4 Survey estimation and analysis techniques Survey estimation and analysis techniques are available that can take all three key features of the study design into account and many of these techniques are now included in commercially available software Incorporating the study design features into analyses of the study can produce externally valid results at the full population level Estimates of means proportions and totals incorporating the study design provide the best estimate of the true means proportions and totals within the total population Analytic techniques particularly modelling aim at exploring relationships within the data are able to estimate the best fitting model for the underlying population not just the best fitting model for the sample when properly applied to account for the study design 13 1 5 Useful references An overview of population survey methods is given by Levy and Lemeshow 1999 They discuss the use of stratification weighting and clustering in survey design and the impact it has on the analysis of sample survey data For a thorough discussion of the mathematical techniques used to analyse data from complex surveys see Chambers and Skinner 2003 13 1 6 Software There is now a range of software available from a number of vendors that supports the analysis of data from complex survey designs incorp
87. oodman UK 1999 7 4 Derived variables The derived items start with an age indicator as outlined in section 7 3 1 followed by an informant or subject indicator and then a mnemonic that relates to the subject matter of the derived item So for example the Peer scale of the SDQ for the K cohort teacher in Wave 2 is dtpeer where d child aged 6 7 years t teacher peer Peer scale of SDQ LSAC Data User Guide November 2013 37 7 5 Study Child Household composition variables In order to keep the variable names under 8 characters it was necessary to have a slightly different convention in the Wave 2 data release Household composition variables have the following structure Where A f xmmm A Child age indicator f f for family Question number numeric x Sub question indicator optional mmm person identifier Note that The age indicator above is as described in section 7 3 1 f is a constant to indicate that it is the household composition that is being described The question number and sub question indicator indicate the question being responded to The person identifier indicates the member number or other identification information For every household the Study Child is Member 1 Wave 1 Parent 1 will be Member 2 and Wave 1 Parent 2 is Member 3 or will be missing if there is no Parent 2 at Wave 1 Any additional people in the household at the time of Wave 1 are given Member numb
88. or by selecting Data gt Filter gt Show from the menus More advanced searches can be performed using the Custom Filter option which produces a dialogue box to assist with your searching For example to find all the questions that contain the word internet go to the question column and open up the filter menu and click on Custom filter in the dialogue box change equals to contains and type internet next to this LSAC Data User Guide November 2013 47 Figure 5 Example of filtering in Excel eoo OB w E New Open Save Print Import Copy Paste Format Undo Redo AutoSum Sort A Z Sort Verdana BE OA 8 lt 9 lt gt A B File Variable Without 1 Order File Cohort 2 Sort Ascending Sort Descending 18981 18980 id37b 1 Show All 18982 18981 oW 0010 5 id37b1 1 34 Custom Filter BO 18983 18982 id37b2 B3 18984 18983 id37b3 B6 18985 18984 xis id37b4 K4 K6 K7 IE ETT 18985 K8 id37b5 K9 BEES m 8 3 2 Using wildcards for filtering A good understanding of the variable naming convention is valuable for using the Data Dictionary Both the on line and Excel Data Dictionary can be searched and filtered using wildcards which can be used to return thematically linked sets of variables Two wildcard characters are used by both these programs
89. orating stratification clustering and weighting These include SAS using the SURVEYMEANS and SURVEYREG procedures STATA using the svy commands and SPSS through the SPSS Complex Samples add on module as well as software packages specifically designed for the analysis of sample survey data such as WesVar and SUDAAN Use of the appropriate analytic techniques from one or more of these packages is recommended for researchers analysing the LSAC data Results that properly account for the sample design features will have the greatest external validity and should be appropriate for drawing inferences about the total population of children from which the sample was drawn LSAC Data User Guide November 2013 69 A template for using the SURVEYREG and SURVEYMEANS procedures in SAS is shown in Figure 7 Figure 7 SURVEYREG and SURVEYMEANS procedures in SAS proc surveyreg data lt filename gt total lt stratumfile gt stratum stratum cluster pcodes model lt standard SAS model details gt weight weights run proc surveymeans data lt filename gt total lt stratumfile gt stratum stratum cluster pcodes var lt variable names gt weight weights run Where stratum is a variable you can calculate for 0 using the formula stratum int mod hicid 10000000 1 00000 pcodes is the postcode of selection already on the data file weights is the sample weight preferred to the population weight for this analysis
90. owing items have response categories collapsed i e response categories combined to form an aggregate category Parents occupation output at 2 digit Australian Standard Classification of Occupations ASCO level or rounded off to the nearest 5 if ANU 4 ratings of occupational prestige Occupation in previous job output at 2 digit ASCO level Socio Economic Index for Areas SEIFA variables rounded to the nearest 10 Country of birth coded as 0 if fewer than five contributors Religion coded as if fewer than five contributors Language Other Than English LOTE coded as 0 if fewer than five respondents The following data items are top coded Income Housing costs Child support paid by Parent 2 Children and Parent s current height weight and waist circumference Number of hours spent in childcare LSAC Data User Guide November 2013 52 11 Data imputation Limited imputation of data is undertaken in LSAC In general imputation occurs only when there is clear contradiction between data items and there is a good reason to believe one item over the other Some basic principles are applied for this task 11 1 1 Virtual roll forward Roll forward is the term in CAI design that refers to the use of data from a previous wave of data collection to determine the questions that need to be asked in a subsequent wave For Wave 2 a limited set of data was rolled forward largely to assist with the household composi
91. p so SAS runs the above statements LSAC Data User Guide November 2013 25 Statements 10 13 produce the means of the variables in the array which SAS gives the names Tveatl to Tveat96 by default The mean here will be the percentage of children from whom an activity was known that ate or drank in front of the TV etc at each time period Line 12 uses the day weight variable bweightd to ensure the proportion is representative of the population and represents each day of the week equally 1 data diary2 2 set mtud diary2 3 array x 96 40 b2da0101 b2de0196 4 array Tveat 96 5 do i 1 to 96 6 if 1 4 1 and x i 12 1 then Tveat i 100 7 else if x i 4 0 or x 1 12 20 and 1 1 1 then Tveat i 0 8 end 9 run 10 proc means data diary2 11 var Tveat1 Tveat96 12 weight bweightd 13 run This data can be used to produce a graph known as a tempogram Figure 1 shows the data produced by the example program along with the equivalent data for the K cohort at Waves 1 and 2 It shows that children did more of this as they got older and that this activity was most common in the early mornings Figure 1 Tempogram of children watching TV video DVD or movies while eating or drinking by wave and cohort W2B WiK W2K Percentage LSAC Data User Guide November 2013 26 SPSS The equivalent code to derive the t
92. present when the child was aged 4 5 or whether there was a Parent 2 at all in Wave 1 for the K cohort c child aged 4 5 01 present for wave m3 Wave 1 Parent 2 e af08am Relationship of the Mother when the child was aged 0 1 to the Study Child a ages0 l f family O8 relationship to study child am mother of child at age 0 1 e dfOlcpl Whether the Parent 1 of the child when aged 4 5 is present in the household when the child is aged 6 7 d child aged 6 7 f family 01 present for wave cpl child s Parent 1 when child is aged 4 5 e cfl3dp2 Whether the Parent 2 of the child when aged 6 7 had a medical condition or disability at the time the child was 4 5 c child aged 4 5 f family 13 whether person has a disability dp2 Parent 2 when child is aged 6 7 Table 7 shows the information that is available for each person LSAC Data User Guide November 2013 39 Table 7 Question numbers used in variable names for household member characteristics x Question 01 Present for wave 02 Gender 03 Age 04 DOB 05 Temporarily away from home as per Wave 1 question 06 Relationship to parent 1 07 Relationship to parent 2 08 Relationship to study child 09 Country of Birth 10 Year of first arrival in Australia 11 Language other than English spoken at home 12 ATSI status 13 Has a condition or disability for 6 months or more as per Wave 1 question 13a lstspecific condition 13b 2nd specific condition
93. r information provided in the questionnaire Parental income Outlying values particularly those with responses to other questions e g categorical income sources of income that make the income value appear incorrect were adjusted Parental height It was found that there were some changes in height between waves for some parents of study children While most were minor most likely due to estimation error some were more substantial and called into question the reliability of differences in Body Mass Index recordings between waves Time Use Diary data Responses were recorded by marking an oval which indicated whether an activity situation occurred in each 15 minutes time period A number of false positives were discovered in the Wave 1 TUD data Imputation was used to reduce the number of false positives A number of imputations were also performed to improve data quality in all three waves Further details of these imputations are given in the Data Issues papers LSAC Data User Guide November 2013 54 12 Survey Methodology LSAC employs a cross sequential design that follows two cohorts of children initially aged 0 1 years B cohort and 4 5 year olds K cohort in 2004 Families are visited by interviewers every two years to collect data for the main waves of the study In the between years a mail out survey was conducted to help maintain contact with families and obtain some additional information at Waves 1 5 2 5
94. re card i e service is initially incorrectly recorded against someone else on the same card e provider has issued an amended account or e anew cheque has been issued to replace lost stolen un presented cheques In relation to small benefits e there are a number of item numbers which have small benefits e g many pathology related claims e there are also small amounts for things like bulk bill incentives generally around 5 6 or e the claimant had reached the Medicare Safety Net MSN threshold Once the threshold has been reached the family s out of pocket expenses are tallied and a payment is calculated for a percentage of the substantiated amounts In effect there can be two payments made for the same doctor s visit one to the doctor for the service and one to the claimant for MSN purposes LSAC Data User Guide November 2013 28 7 2 10 3 PBS file The final of these datasets contains the PBS data Again each record represents a benefit claim Records are available for medications supplied between May 2002 or birth for the B cohort and early 2013 The following information is included for each record Child identification number Item code Item name Quantity Benefit paid Prescription type original repeat or unknown Payment category Payment status Date of payment Date of supply 7 2 10 4 Example derivations There are simple techniques in SAS SPSS and STATA to summarise across multiple r
95. re programs in centres schools occasional care programs multi purpose centres and other arrangements e The Teacher Questionnaire TQ is for children aged 4 5 years and older who attend a school or for some 4 5 years olds a preschool or long day care centre e Interviewers make observations IOBS with permission of the respondent about the interview state of the house where the interview was conducted and the neighbourhood characteristics of where the respondent lives e In Wave 1 the Australian Early Development Index AEDI was included as a nested study which involved the AEDI questionnaire being sent with the K cohort LSAC Teacher Questionnaire in Victoria Queensland and Western Australia The AEDI is a community level measure of young children s development based on a teacher completed checklist It consists of over 100 questions measuring five developmental domains language and cognitive skills emotional maturity physical health and wellbeing communication skills and general knowledge and social competence More information on the AEDI can be found on the following website http www rch org au australianedi edi cfm doc_id 6211 e The Family Contact Form FCF recorded information about any contact between the interviewer and the family of each of the selected children at the time of Wave 1 regardless of whether they agreed to participate in the study or not The information was mainly used by the fieldwork agency with the o
96. riables as well It should be noted that Parent 1 and Parent 2 may be the guardians of the child and not the child s biological parent so in this context Mother should be taken to mean female parent guardian Sometimes Parent 1 and or Parent 2 might change between waves For instance Parent 1 may be female in both waves but different people If there are two female parents Parent 1 is coded as Mother and Parent 2 is coded as Father This will be maintained if the parents swap who Parent 1 and Parent 2 are in subsequent waves This means that there are a small number of female Fathers that analysts should be mindful of when working with these variables LSAC Data User Guide November 2013 9 5 Instruments The following table summaries the data collection instruments used in each wave Table 1 Data collection modes by wave Questionnaire Mode Completed Indicator WI W2 W3 WA w5 by Variable Face to Face Paper Parent 1 N A BK Interview F2F Face to Face Computer Parent 1 N A BK BK BK BK Interview F2F Parent 1 during Paper Parent 1 pldd BK BK BK interview P1D Parent 1 during Computer Parent 1 pldd BK BK interview CASI Parent 1 Leave behind Paper Parent 1 plsed BK BK BK P1L Parent 2 Leave behind Paper Parent 2 p2scd BK BK BK BK BK P2L Child Self Report Computer Study Child csrd K K B BK CSR Audio
97. rther understanding of child development inform social policy debate and be used to identify opportunities for intervention and prevention strategies in policy areas concerning children and their families 4 1 Objectives LSAC explores family and social issues and addresses a range of research questions about children s development and wellbeing Information is collected on the children s physical and mental health education and social cognitive and emotional development from parents child carers pre school and school teachers and the children themselves Its longitudinal structure enables researchers to determine critical periods for the provision of services and welfare support and identify the long term consequences of policy innovations see LSAC Discussion Paper No 1 Introducing the Longitudinal Study of Australian Children for more details LSAC aims to provide a database for a comprehensive understanding of children s development in Australia s current social economic and cultural environment LSAC is delivering the first ever comprehensive national Australian data on children as they grow up 4 2 Who is involved Growing Up in Australia the Longitudinal Study of Australian Children is conducted in partnership between the Department of Social Services DSS the Australian Institute of Family Studies the Institute and the Australian Bureau of Statistics ABS with advice provided by a consortium of leading researc
98. s 1 Excellent 2 No 2 Very good 2 Don t know 3 Good 4 Fair If SC needs or uses more medical care mental 5 Poor health or educational services than is usual for 2 Don t know most children of the same age If hs14d 1 8 2 Frequencies The frequencies are a listing of the response categories for each question and the number of cases in each category Figure 4 provides an example of the listing Figure 4 Example of the weighted frequencies 0 1 P1 F2F 1 1 Main activity FT work apwOlal Frequency Percent Cumulative Cumulative Frequency Percent 4 1 636675 0 03 1 636675 0 03 No 4763 971 93 28 4765 608 93 32 Yes 341 3922 6 68 5107 100 00 The frequencies are useful for simple queries related to particular questions for example how many births were a normal delivery or what are the codes used for Wave 1 question A15 Variables for which there were a wide variety of responses meaning unaltered frequencies would run for several pages eg Study Child weight have been rounded off to enable grouping of responses 8 3 Data Dictionary This is available as both an online version and in Excel Both versions of the data dictionary are searchable and can be sorted Each record describes a single variable and has the following fields variable name variable name without age useful for sorting LSAC Data User Guide November 2013 46 topic number allows derived items to be sorted i
99. s discussed below The following methods are used to collect study data e The Face to Face Interview F2F is conducted with Parent 1 although in Wave 1 Parent 2 could complete some sections if this was more convenient This component is undertaken with all participating families at wave Some interviews might be completed over the telephone in full and refer to p 56 remote areas e The Parent 1 During Interview Questionnaire PID consists of self complete items for which it was considered important to achieve high response rates In Wave 4 it became a Computer Assisted Self Interview CASI e The Parent 1 Leave Behind Questionnaire P1L consists of lower priority self complete items Efforts are made to obtain this data from Parent 1 while the interviewer is in the home This form became part of the CASI e The Parent 2 Leave Behind Questionnaire P2L consists of self complete items Efforts are made to obtain this data from Parent 2 while the interviewer is in the home If this is not possible the questionnaire is left for completion at a later time e Child Self Report Interview CSR consists of items answered by the Study Child For children younger than 10 years old it is administered by an interviewer For LSAC Data User Guide November 2013 11 children 10 years old and older it is administered via Audio Computer Assisted Self Interview ACASI As part of the interview physical measurements are taken and other as
100. s speaking English only at home Percentage of persons with ATSI origins Percentage of persons completed year 12 Percentage of persons above median income category Percentage of persons working Percentage of households with internet capacity in 2006 Census only Percentage of households with broadband in 2006 Census only Census data is either linked at the Statistical Local Area SLA level or where this wasn t available the child s postcode One estimate is provided for each time point representing a linear interpolation of the data at the censuses either side of the time period For example if a SLA had 4 296 of people with ATSI origins in 2001 and 6 5 with ATSI origins in 2006 then the estimate for the proportion in 2004 would be lime since census estimate 2001Data 2006Data 2001Data time between censuses estimate 4 2964 6 5 4 2 x 2004 2000 2006 2001 estimate 4 2 4 2 39 x 0 6 estimate 5 694 Since the CBC or HBC forms were only dispatched to the child s main care type each child could only have one of these completed for them Hence for Waves 1 and 2 HBC and CBC data are merged into a single set of variables where possible This data is given in the order of the HBC questionnaire with questions appearing only in the CBC form given at the end LSAC Data User Guide November 2013 22 If data is only available for one of the Censuses then no interpolation is performed A l
101. sehold member characteristics x Question 01 Present for wave 02 Gender 03 Age 04 DOB 05 Temporarily away from home as per Wave 1 question 06a Relationship to PLE 08 Relationship to study child 09 Country of Birth 10 Year of first arrival in Australia 11 Main language spoken at home 12 ATSI status LSAC Data User Guide November 2013 41 PLE household file also includes the following variables asterisk refers to child age indicator datplec date of PLE PLE CATI interview e plepar whether PLE has a partner e pleparmn PLE partner member number in PLE household e dfd02p3 date of recent PLE marriage e dfd02p4 date of PLE cohabitation 7 7 Age invariant indicator variables There are 5 variables at the start of each of the main data files which contain no age indicator These are hicid unique identifier assigned when child was selected by Medicare Australia cohort wave stratum stratum at the time of selection pcodes postcode at the time of selection Users wishing to create long datasets should note the presence of these variables when removing age indicators 7 7 1 Study child unique identifier Each study child has a single unique identification variable to ensure matching and merging across instruments files and waves This number was allocated at the time of selection by Medicare Australia The first digit indicates which cohort the child is in 1 4 Infa
102. sessments such as measures of cognition or achievement administered to the Study Child e The Study Child completes an Audio Computer Assisted Self Interview ACASI by themselves This method allows sensitive content to be answered by the child in total anonymity e The Time Use Diary TUD documents a 24 hour period of the child s life In Waves 1 2 and 3 the child s family were asked to complete two TUDs one for a weekday and one for a weekend day A different procedure was implemented in Wave 4 In Wave 4 the Study Child K cohort only was asked to complete one TUD A TUD form with instructions on how and when to fill it in was sent to the study child prior to the interview The study child was asked to fill in the TUD form on the day before the interview date The next day during the interview the interviewer asked the child to describe yesterday using the TUD form The day the diary referred to could be any day of the week depending on when the interview was scheduled e The Parent Living Elsewhere Questionnaire PLE was first included in Wave 2 as a mail back questionnaire In Wave 3 it became a Computer Assisted Telephone Interview CATI e The Home Based Carer Questionnaire HBC is for children aged 0 1 and 2 3 years who receive childcare in a home environment most commonly from a grandparent The Centre Based Carer Questionnaire CBC is for children aged 0 1 and 2 3 years who receive childcare from long day ca
103. sistance was gained to identify whether families were in residence and willing to be interviewed Travel to remote communities was only undertaken if there was an appointment for an interview Aboriginal and Torres Strait Islander families are included in representative numbers in non remote centres However there has been a higher rate of attrition from the study among these families See the weighting and non response technical papers for more details www aifs gov au growingup pubs technical index html 12 3 7 Remote areas In the initial sample there were 12 postcodes selected in areas classified as remote by the ABS Australian Standard Geographic Classification ASGC Remoteness Classification Interviewers were either recruited from these areas or travelled to these areas when the field agency did not have a suitable interviewer in the locality Where visits were not possible telephone interviews were conducted 12 in Wave 1 42 in Wave 2 87 in Wave 3 83 in Wave 4 and 73 in Wave 5 The increasing number is due to sample dispersion LSAC Data User Guide November 2013 61 12 4 Fieldwork response 12 4 1 Wave 1 recruitment The final response to the recruitment of children was 54 per cent of those families who were sent the initial letter by Medicare Australia The response rate was higher for the B cohort with 57 per cent of families 5 107 agreeing to take part compared with 50 per cent of K cohort families 4 983 A
104. stcode to both reduce field enumeration costs and allow the study of community level effects on children s development and wellbeing and e weighting to adjust for potential non response bias and to provide population estimates e It is the responsibility of data users to determine when and how each of these needs to be accounted for when developing their analyses 13 1 1 Stratification Stratification by state and part of state was employed to ensure that all geographic areas within Australia are represented in the sample in proportion to their population This produces a more even distribution of the sample across geographic areas than could be expected from a simple random sample The use of stratification can be expected to reduce standard errors compared with a simple random sample with no control over the geographic spread of the sample As such when trying to extrapolate to the population the stratification should be incorporated in the analysis of results from the survey in order to correctly calculate standard errors and confidence intervals LSAC Data User Guide November 2013 64 13 1 2 Clustering The use of clustering in the sample design has important consequences for the analysis of data from the study Clustering is useful in reducing the field costs associated with the survey enumeration Clustering also has the added benefit of making possible the analysis of community level effects by ensuring that sufficient sample
105. sted Study LSAC Data User Guide November 2013 34 Abbreviation Topic Scope pw Paid Work Information on work status such as employment occupation and work family interactions re Relationships Information on the quality of relationships primarily focused on the relationship between Parent 1 and Parent 2 but also on broader family harmony SC Social Capital Information on social capital such as attitudes to neighbours their neighbourhood and use of Services se Social and Information relevant to the social and emotional Emotional development of the child such as temperament Outcomes behaviour and emotional states tp Teaching Practices employed by teachers and childcare Practices workers in their work such as time use use of resources and general philosophies For example e 01 Parent 1 rating of self efficacy has pa as the second and third letters as its topic is Parenting and e zhs03a Birth weight of study child has hs as the second and third letter as its topic is Health Status 7 3 3 Specific question identifier alphanumeric The last 5 digits of a variable name make up the specific question identifier These digits contain whatever information is necessary to uniquely identify each item Each has an arbitrary two digit question number not related to the questionnaire positioning Items of related content are grouped together as much as possible
106. t child population weights is 243 026 and the sum of the K cohort child population weights is 253 202 which are the ABS estimated resident population counts of children aged O years and 4 years respectively at end March 2004 adjusted for the remote parts of Australia that were excluded from the study design e Child sample weight this is the child population weight rescaled such that the sum of the weights matches the number of children in the sample e g 5 107 B cohort and 4 983 K cohort in Wave 1 This weight is used in analyses that expect the weights to sum to the sample size rather than the population particularly when tests of statistical significance are involved e Time Use Data day weight for Waves 1 2 and 3 only this is the sample weight adjusted so that each day of the week receives equal weight in analyses of time use data Data files for Wave 1 and Wave 2 each have one population weight and one sample weight Given that there are no cases that responded to Wave 2 that didn t respond to Wave 1 these weights can be used for both longitudinal and cross sectional analyses At Wave 3 two sample weights and two population weights are necessary as this is the first time that respondents could return to the study after missing a wave The first of these weights the full Wave 3 sample and should be used for cross sectional analyses The second weights the sample that has responded to all three waves and should be used for
107. t from five different options The data file includes raw scores number of correct responses and scaled scores based on age norms given in the WISC IV manual The instrument comprises 35 items of increasing complexity Children start on the item corresponding to their age appropriate start point If a child does not answer correctly on the first or second start point items the examiner should ask two items prior to the age appropriate start point called reverse administration Reverse administration was not implemented in the LSAC instrument See the discussion of this issue in Data Issue Paper No 8 available from the study website http www growingupinaustralia gov au pubs issues index html The Wechsler Intelligence Scale for Children Fourth Edition is copyrighted by Harcourt Assessment Inc 2004 LSAC Data User Guide November 2013 15 5 2 Response rates The number and percentages of survey instruments of each type that were completed at each wave is shown in Table 2 More detailed information on non response can be found in the Weighting and non response technical papers Table 2 Waves 1 5 instrument response B cohort K cohort Wave 1 Instrument a Eligible b Actual c Eligible b Actual c _ 5107 5107 100 4983 4983 100 PIE _ 5107 4341 85 4983 4229 85 P E 4630 3696 80 4286 3388 NS TUD 1 _ 5107 4031 79 4983 3867 78 TUD 2 5107 3751 73 4983 3582 oO Nn
108. t happened yet In these cases the time of the previous wave is treated as the time of the event For example if a parent reported at Wave 2 that the child stopped being breastfed after two months however at Wave 1 the child was three months old and was reported as still being breastfed the age of breastfeeding cessation would be set to three months This strategy for fixing the time of an event is also used for e Date when new members joined the household e Length of attendance at a particular childcare facility e Date left the household for Wave 1 members and temporary members bfl4ml bf14m2 etc e Age stopped breastfeeding zf05c e Age first had non breast milk zhb07 e Age first had solid food zhb10 e Age entered child care arrangements bpc11a bpc11b etc e Age last lived with 2 biological parents bpe23c LSAC Data User Guide November 2013 53 11 1 3 Other imputations On inspection of the data problems were revealed in a small number of items that were solved using imputation Employment status some assumptions are made to assist in coding the parent to employed unemployed or not in the labour force where missing values were present Type of educational program K cohort Wave 1 There appeared to be some confusion with parents and interviewers as to whether the child was in pre school or 1 at school The type of education program variable was amended based on the teacher data and othe
109. te of Applied Economic and Social Research University of Melbourne Willms D Eds 2002 Vulnerable Children University of Alberta Press Edmonton Wooden M 2001 Design and Management of a Household Panel Survey Lessons from the International Experience HILDA project discussion paper series The Melbourne Institute of Applied Economic and Social Research University of Melbourne Wooden M amp Watson N 2000 The Household Income and Labour Dynamics in Australia HILDA Survey An Introduction to the Proposed Survey Design and Plan HILDA project technical paper series The Melbourne Institute of Applied Economic and Social Research University of Melbourne LSAC Data User Guide November 2013 81
110. tion module Time and resource implications meant that roll forward could not be used in some other parts of the questionnaire where it may have reduced respondent burden For example in Wave 2 respondents were again asked about the age the child stopped being breastfed in order to obtain the information from those cases where this had not yet happened at the time of Wave 1 In re asking this question some respondents gave different answers to their Wave responses Given that recollection of respondents is likely to be more accurate closer to the event i e the cessation of breastfeeding it was decided that in cases where Wave 1 data exists the Wave 1 value is taken as correct and the Wave 2 value is ignored i e as if the Wave 1 data had been rolled forward and the question never asked in Wave 2 This means a single variable 1s produced that represents the best estimate from the two waves of data Users are able to tell at which wave the timing data was collected by referring to the question from each wave asking if the child is still being breastfed Note From Wave 3 onwards there is a greater use of roll forward which reduced the number of situations where such conflicts could occur 11 1 2 Longitudinal contradictions Another possible contradiction in the data may occur where respondents report at a subsequent wave that an event occurred at a time before a previous wave when the previous wave s data indicated that this event hadn
111. tre Sanson A Misson S amp The LSAC Outcome Index Working Group 2006 Summarising children s well being the LSAC Outcome Index LSAC Technical Paper No 2 Australian Institute of Family Studies Melbourne Sanson A Nicholson J Ungerer J Zubrick S Wilson K Ainley Wake M 2002 Introducing the Longitudinal Study of Australian Children LSAC Discussion Paper No 1 Australian Institute of Family Studies Melbourne Sipthorp M amp Misson S 2009 Wave 3 Weighting and non response LSAC Technical Paper No 6 Australian Institute of Family Studies Melbourne Soloff C Lawrence D amp Johnstone R 2005 Sample Design LSAC Technical Paper No 1 Australian Institute of Family Studies Melbourne Soloff C Lawrence D Misson S amp Johnstone R 2005 Wave 1 weighting and non response LSAC Technical Paper No 3 Australian Institute of Family Studies Melbourne LSAC Data User Guide November 2013 79 16 Bibliography The following publications provide more information on techniques for analysis longitudinal and survey data Australian Bureau of Statistics 1996 Women s Safety Australia User Guide Chambers R L amp Skinner C J Eds 2003 Analysis of Survey Data Chichester Wiley Deville J C amp Sarndal C E 1992 Calibration estimators in survey sampling Journal of the American Statistical Association 87 376 382 Deville J C Sar
112. tures was used The child points to or says the number of a picture that best represents the meaning of the word read out by the interviewer Scores are created via Rasch Modelling so that changes in scores represent real changes in functioning rather than just changes in position relative to peers See the Data Issues Paper No 2 for more details available on the study website http www growingupinaustralia gov au pubs issues index html The Who Am I is copyrighted by Australian Council for Educational Research Melbourne 1999 The Peabody Picture Vocabulary Test Third Edition PPVT III Form is copyrighted by Lloyd Dunn Leota Dunn Douglass Dunn American Guidance Service Inc 1997 and published exclusively by AGS Publishing Permission to adapt and create a short form for LSAC was granted by the publisher The PPVT III LSAC Australian Short form was developed by S Rothman Australian Council for Educational Research ACER Melbourne from the Peabody Picture Vocabulary Test Third Edition PPVT III Form English edition LSAC Data User Guide November 2013 14 5 1 4 Matrix Reasoning Children completed the Matrix Reasoning MR test from the Wechsler Intelligence Scale for Children 4th edition WISC IV at ages 6 7 8 9 and 10 11 years This test of non verbal intelligence presents the child with an incomplete set of diagrams an item and requires them to select the picture that completes the se
113. turned d Response rates for Wave 2 Wave 3 Wave 4 or Wave 5 as a proportion of Wave families 5 21 Parent 1 Questionnaires In Wave 1 interviewers encouraged the parents to complete the PIL and P2L forms while the interviewer was in the home Interviewers were also able to pick up forms in some cases when forms were left behind Forms not given to interviewers were mailed back Two reminders were made for forms that were not returned In Wave 2 Parent 1 had two forms to complete Interviewers were instructed that the P1D form must be completed when they were in the home resulting in a high response rate The PIL was generally left behind for mail back as there was not enough time for these to be completed as well Interviewers were generally not required to pick up the forms Up to four reminders were made for forms that were not returned however the PIL forms showed lower response rates in Wave 2 LSAC Data User Guide November 2013 17 compared with Wave 1 This may be because P1 had already completed one form and also because interviewers did not generally pick up forms For Wave 3 there was only one Parent 1 self complete form Interviewers were instructed that this form must be completed while the interviewer was in the home However only two thirds of parents were able to do so Three reminders were given for forms not returned In Wave 4 Parent 1 was asked to complete a CASI which resulted in a response rate of 9
114. uld dictate another scoring system This enabled the calculation of scale level derivations where data measuring a construct has multiple contributing data items and where some contributing items are missing Using a sum calculation for these scales would have lead to the exclusion of cases with any missing data All contributing data items to these scales are included on the datasets For scales where there are different sets of items for children at different ages or for different informants multiple versions of the same scale are calculated based on just those items shared between two versions of the scale For example the parenting hostility scale began as a 5 item measure for 0 1 year olds but had one item dropped for children aged 4 7 years and a further item dropped for children aged 8 9 years LSAC Data User Guide November 2013 50 the file for 0 1 year olds three different versions of the scale are calculated one using all 5 items another just using the 4 items included for children aged 4 7 years and another using just those 3 items used for children aged 8 9 years As a general rule data users should select the variable containing the greatest number of contributing items that is appropriate for their purpose So for analyses just using the hostility scale at aged 0 1 years or for those comparing the hostility scale at ages 0 1 and 2 3 years analysts should use the 5 item version For analysts comparing hostility between th
115. veat variable in SPSS would look like do repeat eat b2da0401 b2da0402 b2da0496 tv b2da1201 2 1201 b2da1296 dk b2da0101 b2da0101 b2da0196 tveatl to tveat96 if eat 1 or tv 1 tve 1 if eat 0 or tv 0 and dk 0 tve 0 end repeat STATA The equivalent code to derive the tveat variable in STATA would look like 7 2 2 foreach n of numlist 1 9 7 2 3 gentveat n z1 if b2da040 n 1 amp b2dal20 n 1 7 2 4 replace tveat n 20 if b2da040 n 0 b2dal20 n 0 b2da010 n 0 7 2 5 7 2 6 foreach n of numlist 10 96 7 2 7 gen tveatn 1 if bD2da04 n 2 1 amp 2 2 n 1 7 2 8 replace tveat n 20 if D2da04 n 2z0 b2da12 n 220 amp b2da01 n 2 0 7 2 9 7 2 10 Medicare Australia data In Wave 1 97 of parents of study children gave consent for their children s data to be linked with Medicare Australia data for the duration of the study This includes data from the Medicare Benefit Scheme MBS the Pharmaceutical Benefit Scheme PBS and the Australian Childhood Immunisation Records ACIR Data from these sources provide an indication of usage history of MBS PBS and ACIR services Linkage was successful for 93 of children incomplete consent forms resulted in data not being released for about 400 children Since the child s use of medical services is ongoing the Medicare Australia data are not broken into waves but are provided as three separate files e ACIR Each record in t

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