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1. 2 An adjustment to account for the additional non response to the supplementary survey i e non response to the OMDS households that did respond to the LFS The procedure is similar to the LFS non response weight adjustment but groupings are based on different variables At this stage the weight is comprised of two components the inverse of the sampling rate and the non response adjustment A third component the family weighting adjustment described below was added to improve accuracy of estimates Independent estimates are available monthly for various age and sex groups by province These are population projections based on the most recent census data records of births and deaths and estimates of migration Using a linear regression model auxiliary information is used to arrive at the final weight The regression is set up to ensure that the final weights it produces sum to the census projections for the auxiliary variables namely various age sex groups economic regions and census metropolitan areas This improves the reliability of estimates that can be produced by the OMDS At the same time as ensuring consistency with external census counts the family weighting procedure also ensures that every member of the economic family is assigned the same weight Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide The Master file has been created at the person level and consequently the weights on the fi
2. For example in the urban area frame sample yields are either six or eight dwellings depending on the size of the city In the urban apartment frame each cluster yields five dwellings while in the rural areas and EA parts of cities each cluster yields 10 dwellings In all clusters dwellings are sampled systematically This represents the final stage of sampling 5 2 6 Person Selection Demographic information is obtained for all persons in a household for whom the selected dwelling is the usual place of residence LFS information is obtained for all civilian household members 15 years of age or older Respondent burden is minimized for the elderly age 70 and over by carrying forward their responses for the initial interview to the subsequent five months in the survey 5 3 Sample Size The sample size of eligible persons in the LFS is determined so as to meet the statistical precision requirements for various labour force characteristics at the provincial and sub provincial level to meet the requirement of federal provincial and municipal governments as well as a host of other data users The monthly LFS sample consists of approximately 60 000 dwellings After excluding dwellings found to be vacant dwellings demolished or converted to non residential uses dwellings containing only ineligible persons dwellings under construction and seasonal dwellings about 54 000 dwellings remain which are occupied by one or more eligible persons Fro
3. Guidelines for Tabulation Analysis and Release This chapter of the documentation outlines the guidelines to be adhered to by users tabulating analyzing publishing or otherwise releasing any data derived from the survey microdata files With the aid of these guidelines users of microdata should be able to produce the same figures as those produced by Statistics Canada and at the same time will be able to develop currently unpublished figures in a manner consistent with these established guidelines 9 1 Rounding Guidelines In order that estimates for publication or other release derived from these microdata files correspond to those produced by Statistics Canada users are urged to adhere to the following guidelines regarding the rounding of such estimates a 9 2 Estimates in the main body of a statistical table are to be rounded to the nearest hundred units using the normal rounding technique In normal rounding if the first or only digit to be dropped is O to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is raised by one For example in normal rounding to the nearest 100 if the last two digits are between 00 and 49 they are changed to 00 and the preceding digit the hundreds digit is left unchanged If the last digits are between 50 and 99 they are changed to 00 and the preceding digit is incremented by 1 Marginal sub totals and totals in
4. as an estimate of an aggregate Example of a Categorical Question Q Do you and your family eat fresh fruit and vegetables every day Yes Q Is this because you cannot afford it or for some other reason R Cannot afford it Some other reason 9 3 2 Quantitative Estimates Quantitative estimates are estimates of totals or of means medians and other measures of central tendency of quantities based upon some or all of the members of the surveyed population They also specifically involve estimates of the form X IY where X isan estimate of surveyed population quantity total and Y isan estimate of the number of persons in the surveyed population contributing to that total quantity An example of a quantitative estimate is the average income of Ontario families who experienced two or more material deprivations Example of a Quantitative Question What is your best estimate of your total income from wages and salaries from all jobs before deductions including tips and commissions during the year ending December 31 2008 9 3 3 Tabulation of Categorical Estimates Estimates of the number of people with a certain characteristic can be obtained from the microdata file by summing the final weights of all records possessing the characteristic s of interest Proportions and ratios of the form X Y are obtained by Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide a summing
5. by province These are population projections based on the most recent census data records of births and deaths and estimates of migration In the final step this auxiliary information is used to transform the sub weight into the final weight This is done using a calibration method This method ensures that the final weights it produces sum to the census projections for the auxiliary variables namely totals for various age sex groups economic regions census metropolitan areas rotation groups household and economic family size Weights are also adjusted so that estimates of the previous month s industry and labour status estimates derived from the present month s sample sum up to the corresponding estimates from the previous month s sample This is called composite estimation The entire adjustment is applied using the generalized regression technique This final weight is normally not used in the weighting for a supplement to the LFS Instead it is the sub weight which is used as explained in the following paragraphs 11 2 Weighting Procedures for the Ontario Material Deprivation Survey The principles behind the calculation of the weights for the OMDS are identical to those for the LFS However further adjustments are made to the LFS sub weights in order to derive a final weight for the individual records on the OMDS microdata file 1 An adjustment to account for the use of a 5 6 five sixth sub sample instead of the full LFS sample
6. counts These clusters are generally a set of one or more city blocks or block faces The selection of a sample of clusters always six or a multiple of six clusters from each of these secondary strata represents the first stage of sampling in most urban areas In some other urban areas census enumeration areas EA are used as clusters In the low density urban strata a three stage design is followed Under this design two towns within a stratum are sampled and then 6 or 24 clusters within each town are sampled For urban apartment strata instead of defining clusters the apartment building is the primary sampling unit Apartment buildings are sampled from the list frame with probability proportional to the number of units in each building Within each of the secondary strata in rural areas where necessary further stratification is carried out in order to reflect the differences among a number of socio economic characteristics within each stratum Within each rural stratum six EAs or two or three groups of EAs are sampled as clusters Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 5 2 5 Dwelling Selection In all three types of areas urban rural and remote areas selected clusters are first visited by enumerators in the field and a listing of all private dwellings in the cluster is prepared From the listing a sample of dwellings is then selected The sample yield depends on the type of stratum
7. design employing probability sampling at all stages of the design The design principles are the same for each province 5 2 1 Primary Stratification Provinces are divided into economic regions ER and employment insurance economic regions EIER ERs are geographic areas of more or less homogeneous economic structure formed on the basis of federal provincial agreements They are relatively stable over time EIERs are also geographic areas and are roughly the same size and number as ERs but they do not share the same definitions Labour force estimates are produced for the EIERs for the use of Human Resources and Skills Development Canada The intersections of the two types of regions form the first level of stratification for the LFS These ER EIER intersections are treated as primary strata and further stratification is carried out within them see Section 5 2 3 Note that a third set of regions census metropolitan areas CMA is also respected by stratification in the current LFS design since each CMA is also an EIER 5 2 2 Types of Areas The primary strata ER EIER intersections are further disaggregated into three types of areas rural urban and remote areas Urban and rural areas are loosely based on the Census definitions of urban and rural with some exceptions to allow for the formation of strata in some areas Urban areas include the largest CMAs down to the smallest villages categorized by the 1991 Census as urban 1 000 peop
8. records by summing the original person weights from the microdata file for these records and then dividing by the number of respondents who reported SEX men 3 for each of these respondents calculate a RESCALED weight equal to the original person weight divided by the AVERAGE weight 4 perform the analysis for these respondents using the RESCALED weight However because the stratification and clustering of the sample s design are still not taken into account the variance estimates calculated in this way are likely to be under estimates The calculation of more precise variance estimates requires detailed knowledge of the design of the survey Such detail cannot be given in this microdata file because of confidentiality Variances that take the complete sample design into account can be calculated for many statistics by Statistics Canada on a cost recovery basis 9 5 Coefficient of Variation Release Guidelines Before releasing and or publishing any estimates from the OMDS users should first determine the quality level of the estimate The quality levels are acceptable marginal and unacceptable Data quality is affected by both sampling and non sampling errors as discussed in Chapter 8 0 However for this purpose the quality level of an estimate will be determined only on the basis of sampling error as reflected by the coefficient of variation as shown in the table below Nonetheless users should be sure to read Chapter 8 0 to be more ful
9. types of non response Complete non response is when the respondent does not provide the minimum set of answers These records are dropped and accounted for in the weighting process see Chapter 11 0 Item non response is when the respondent does not provide an answer to one question but goes on to the next question These are usually handled using the not stated code or are imputed Finally partial non response is when the respondent provides the minimum set of answers but does not finish the interview These records can be handled like either complete non response or multiple item non response In the case of the OMDS donor imputation was used to fill in missing data for non response to the question asking for the total personal income in 2008 Some respondents did not want or were not able to report salary or personal income other than by selecting a range In those cases a conversion to dollar values took place A randomly selected value was imputed in place of a range For the highest open range of 100 000 or more a value of 100 999 was used The data file includes flags indicating where the original response was given as a range or was missing and later imputed Further information on the imputation process is given in Chapter 8 0 Data Quality 7 5 Creation of Derived Variables A number of data items on the microdata file have been derived by combining items on the questionnaire in order to facilitate data analysis A measure of
10. who usually work 30 hours or more per week at their main or only job Part Time Employment Part time employment consists of persons who usually work less then 30 hours per week at their main or only job Economic Family Economic family refers to a group of two or more persons who live in the same dwelling and are related to each other by blood marriage common law or adoption 42 Ontario Material Deprivation Survey Concepts and Definitions Material Deprivation Material deprivation refers to a state where a person or family is without an item or denied an activity deemed to be a necessity because of lack of resources Low Income Cut off LICO The LICO is an income threshold below which a family is expected to spend 20 percentage points more than average on food shelter and clothing The LICOs are calculated separately for different family sizes 1 2 3 4 5 6 and 7 or more members residing in areas of different population size rural urban below 30 000 30 000 to 99 000 100 000 to 499 999 and 500 000 and over Statistics Canada produces before and after tax LICOs for each calendar year For the actual values please see the Statistics Canada s publication Low income cut offs for 2008 and low income measures for 2007 Catalogue no 75F0002M No 002 Area size The area size variable is based on the urban rural status of the enumeration area defined by Statistics Canada in which the majority of the postal codes fall Urban are
11. with the bootstrap method For example although some standard statistical packages allow sampling weights to be incorporated in the analyses the variances that are produced often do not properly take into account the design and or calibration of the weights whereas the Bootstrap variance program does Also for estimates of quantitative variables separate tables are required to determine their sampling error 10 1 Statistical Package for Variance Estimation Statistics Canada has developed a program that can perform bootstrap variance estimation the Bootvar program The Bootvar program is available in SAS or SPSS format It is made up of macros that compute variances for totals ratios differences between ratios and for linear and logistic regression Bootvar may be downloaded from Statistics Canada s Research Data Centre RDC website Users must accept the Bootvar Click Wrap Licence before they can read the files There is a document on the site explaining how to adapt the system to meet users needs SAS http www statcan gc ca rdc cdr bootvar_sas eng htm SPSS http www statcan qc ca rdc cdr bootvar_spss eng htm Income Statistics Division 35 Ontario Material Deprivation Survey 2009 User Guide 11 0 Weighting Since the Ontario Material Deprivation Survey OMDS used a sub sample of the Labour Force Survey LFS sample the derivation of weights for the survey records is clearly tied to the weighting procedure used for t
12. 31 241 Independently in each stratum a simple random sample of n 1 of the n units in the sample is selected with replacement Note that since the selection is with replacement a unit may be chosen more than once This step is repeated R times to form R bootstrap samples For each ofthe R bootstrap samples bootstrap weights are calculated for each unit in the bootstrap sample units not selected in a given bootstrap sample are assigned a weight of zero These bootstrap weights are based on the initial sample design weight the number of times a given unit has been selected and the initial sample size as well as the bootstrap sample size These weights are then adjusted according to the same weighting process as the regular weights non response adjustment calibration etc The entire process selecting simple random samples recalculating weights for each stratum is repeated several times yielding R different bootstrap weights for each unit in the original sample The OMDS uses R 1 000 to produce 1 000 bootstrap samples with 1 000 potential different weights for each unit The end result is 1 000 final bootstrap weights for each unit in the sample The variation among the 1 000 possible estimates based on the 1 000 bootstrap weights are related to the variance of the estimator based on the regular weights and can be used to estimate it There are a number of reasons why a user may need to calculate the coefficient of variation of estimates
13. Estimates 30 9 3 2 Quantitative Estimates 30 9 3 3 Tabulation of Categorical Estimates 30 9 3 4 Tabulation of Quantitative 31 9 4 Guidelines for Statistical Analysis sssssssssseseeeeenenneee enne nnns 31 9 5 Coefficient of Variation Release Guidelines sess 32 Bootstrap Method for Variance esee eene enne nennen nennen nnn annee nn nennen 35 10 1 Statistical Package for Variance Estimation sssssssseeeeennnens 35 Weighting cT 37 11 1 Weighting Procedures for the Labour Force 37 11 2 Weighting Procedures for the Ontario Material Deprivation Survey 38 QUOSTIONNAIIGS ID P 41 12 1 The Labour Force Survey 41 12 2 Ontario Material Deprivation Survey Questionnaire 41 Record Layout with Univariate 5 43 Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 1 0 Introduction The Ontario Material Deprivation Survey OMDS was conducted by Statistics Canada in March and April 2009 with the support of the Cabinet Office of the Government of Ontario This manual has be
14. Microdata User Guide ONTARIO MATERIAL DEPRIVATION SURVEY 2009 Canada Ontario Material Deprivation Survey 2009 User Guide Table of Contents 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 INTO UCTION ec 5 It cerei 7 Objectives are 9 Goncepts and Definiti ns rn dan aie eda ann dee 11 4 1 Labour Force Survey Concepts and Definitions ceres 11 4 2 Ontario Material Deprivation Survey Concepts and Definitions 12 Survey Methodology 13 5 1 Population 13 5 2 SAMP DESIGN Em 13 52 1 Primary es 13 5 2 2 Types of AreaS nunenannnnunnannnnunnannnnnnn nA AeA EENE 13 5 2 3 Secondary Stratification ccoo 14 5 2 4 Cluster Delineation and 14 5 2 5 Dwelling 5 15 5 2 6 Person 15 5 3 He he ON 15 5 4 E Sn E a 15 5 5 Modifications to the Labour Force Survey Design for the Ontario Material Deprivation SU aged 15 5 6 Sample Size for the Ontario Material Deprivation Survey eere 16 Data Coll Ctiony 222270 inp A a fera eA 17 6 1 Interviewing for the Labour Force Survey 17 6 2 Supervision and Quality Control sse enne rr 17 6 3 No
15. The OMDS is based upon a complex sample design with stratification multiple stages of selection and unequal probabilities of selection of respondents Using data from such complex surveys presents problems to analysts because the survey design and the selection probabilities affect the estimation and variance calculation procedures that should be used In order for survey estimates and analyses to be free from bias the survey weights must be used While many analysis procedures found in statistical packages allow weights to be used the meaning or definition of the weight in these procedures may differ from that which is appropriate in a sample survey framework with the result that while in many cases the estimates produced by the packages are correct the variances that are calculated are poor For other analysis techniques for example linear regression logistic regression and analysis of variance a method exists which can make the variances calculated by the standard packages more meaningful by incorporating the unequal probabilities of selection The method rescales the weights so that there is an average weight of 1 For example suppose that analysis of all male respondents is required The steps to rescale the weights are as follows 1 select all respondents from the file who reported SEX men Income Statistics Division 31 32 Ontario Material Deprivation Survey 2009 User Guide 2 calculate the AVERAGE weight for these
16. al non response to the survey occurred when the respondent did not understand or misinterpreted a question refused to answer a question or could not recall the requested information Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide The following table presents response levels to the set of deprivation questions The item non response was very low varying from to 0 8 Although there were some differences between those families who responded to all the deprivation questions and those who did not answer one or more deprivation questions given the fact that the item non response is so low the impact on the final estimates should be negligible The item response rate for the deprivation questions combined with the OMDS response rate was between 88 0 and 88 8 The overall item response rate accounting also for the LFS non response ranged from 83 096 and 83 796 Item response Overall item Deprivation Item rate response rate _ item accounting for accounting for Items Type of Deprivation responding ee OMDS OMDS and LFS households a non response non response Eat fresh fruit and vegetables every day 10 703 0 88 8 83 7 Get dental care if needed 10 673 0 3 88 5 83 5 Eat meat fish or a vegetarian equivalent 10 703 0 88 8 83 7 at least every other day Able to replace or repair broken or damaged appliances such as a vacuum or 10 661 0 4 88 4 83 4 a toa
17. as have minimum population concentrations of 1 000 people and a population density of at least 400 people per square kilometre based on the 2001 Census population counts All the territory outside the urban areas is considered rural Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 5 0 Survey Methodology The Ontario Material Deprivation Survey OMDS was administered in March and April 2009 to a sub sample of the dwellings in the Labour Force Survey LFS sample and therefore its sample design is closely tied to that of the LFS The LFS design is briefly described in the Sections 5 1 to 5 4 Sections 5 5 and 5 6 describe how the OMDS departed from the basic LFS design in March and April 2009 5 1 Population Coverage The LFS is a monthly household survey of a sample of individuals who are representative of the civilian non institutionalized population 15 years of age or older in Canada s 10 provinces Specifically excluded from the survey s coverage are residents of the Yukon Northwest Territories and Nunavut persons living on Indian Reserves full time members of the Canadian Armed Forces and inmates of institutions These groups together represent an exclusion of approximately 296 of the population aged 15 or over 5 2 Sample Design The LFS has undergone an extensive redesign culminating in the introduction of the new design at the end of 1994 The LFS sample is based upon a stratified multi stage
18. casual jobs and those with a job to start at a future date Unemployment Unemployed persons are those who during the reference week a were on temporary layoff during the reference week with the expectation of recall and were available for work or b were without work had actively looked for work in the past four weeks and were available for work or c had a new job to start within four weeks from the reference week and were available for work Not in the Labour Force Persons not in the labour force are those who during the reference week were unwilling or unable to offer or supply labour services under conditions existing in their labour markets that is they were neither employed nor unemployed Work includes any work for pay or profit that is paid work in the context of an employer employee relationship or self employment It also includes unpaid family work which is defined as unpaid work contributing directly to the operation of a farm business or professional practice owned and operated by a related member of the same household Such activities may include keeping books selling products waiting on tables and so on Tasks such as housework or maintenance of the home are not considered unpaid family work N Persons are regarded as available for work if they i reported that they could have worked in the reference week if a suitable job had been offered or if the reason they could not take a job was of a tem
19. e imputed value assigned to the recipient in conjunction with other non imputed items from the recipient would still pass the edit Donor imputation was simultaneously conducted for both personal income and family income Family income was derived by summing the total personal income of all members of a given family There were 341 high income families who were excluded from the donor pool in the donor imputation module for family income Their reported income examined in the context of demographic and labour force characteristics was quite unique so they did not meet the criteria of a good donor Among these families there were 56 with income much higher than expected Their reported income could not be retained and had to be imputed The cases of imputation of personal income include records where it was imputed for 54 individuals who belonged to families with 5 or more adults Their income information was missing because to reduce response burden personal income was collected for a maximum of 4 family members aged 15 and over Step 1 Personal Income Step 2 Family Income Imputed 2 747 1 679 Total 21 529 10 703 Rate 12 8 15 7 The OMDS imputation process worked well A flag indicating which records had imputed income values is included on the Master File 8 2 5 Measurement of Sampling Error Since it is an unavoidable fact that estimates from a sample survey are subject to sampling error sound statistica
20. eights of responding households The weight of each responding record is increased by the ratio of the number of households that should have been interviewed divided by the number that were actually interviewed This adjustment is done separately for non response areas which are defined by employment insurance economic region type of area and rotation group It is based on the assumption that the households that have been interviewed represent the characteristics of those that should have been interviewed within a non response area Income Statistics Division 37 Ontario Material Deprivation Survey 2009 User Guide 38 Labour Force Survey Sub weight The product of the previously described weighting factors is called the LFS sub weight All members of the same sampled dwelling have the same sub weight Sub provincial and Province Age Sex Adjustments The sub weight can be used to derive a valid estimate of any characteristic for which information is collected by the LFS However these estimates will be based on a frame that contains some information that may be several years out of date and therefore not representative of the current population Through the use of more up to date auxiliary information about the target population the sample weights are adjusted to improve both the precision of the estimates and the sample s representation of the current population Independent estimates are available monthly for various age and sex groups
21. en produced to facilitate the manipulation of the microdata file based on the survey results Any question about the dataset or its use should be directed to Statistics Canada Andrew Heisz Income Statistics Division Telephone 613 951 3748 Fax 613 951 0080 E mail Andrew Heisz Ostatcan gc ca Client Services Income Statistics Division Telephone 613 951 7355 or call toll free 1 888 297 7355 Fax 613 951 3012 E mail income Q statcan gc ca Cabinet Office of the Government of Ontario Bruce Baldwin Executive Coordinator Health Social Education and Children s Policy Cabinet Office 99 Wellesley St WI Rm 4340 Toronto Ontario M7A 1A1 Telephone 416 325 7801 E mail Bruce Baldwin ontario ca Income Statistics Division 5 Ontario Material Deprivation Survey 2009 User Guide 2 0 Background The Ontario Material Deprivation Survey OMDS was conducted on behalf of the Ontario Government The aim is to gauge the ability of families to satisfy basic material needs such as food clothing housing as well as social needs of participation and leisure The survey includes ten items deemed to be necessities due to lack of resources The list of ten items comes from a 2008 study by the Daily Bread Food Bank of Toronto lt also includes questions on income The OMDS was fielded in March and April 2009 as a supplement to the Labour Force Survey Income Statistics Division Ontario Material Deprivation Surv
22. ey 2009 User Guide 3 0 Objectives The survey was designed to produce estimates of the incidence of missing two or more items out of ten for Ontario and various geographic subgroups Estimates were to be produced at the individual level It was also designed to provide contextual data on demographic and socioeconomic characteristics of Ontario families and individuals Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 4 0 Concepts and Definitions This chapter outlines concepts and definitions of interest to the users The concepts and definitions used in the Labour Force Survey LFS are described in Section 4 1 while those specific to the Ontario Material Deprivation Survey OMDS are given in Section 4 2 Users are referred to Chapter 12 0 of this document for a copy of the actual survey questionnaire s used 4 1 Labour Force Survey Concepts and Definitions Labour Force Status Designates the status of the respondent vis vis the labour market a member of the non institutional population 15 years of age and over is either employed unemployed or not in the labour force Employment Employed persons are those who during the reference week a did any work at all at a job or business or b hada job but not at work due to factors such as own illness or disability personal or family responsibilities vacation labour dispute or other reasons excluding persons on layoff between
23. f them was randomly selected to participate in the OMDS While the LFS carries forward information obtained during the initial interviews the OMDS collected information from and about persons 70 years of age and over as well as members of the armed forces not living on military bases 5 6 Sample Size for the Ontario Material Deprivation Survey The following table shows the number of economic families as well as persons 15 years of age and older in the LFS sampled rotations who were eligible for the OMDS supplement This table includes households which were non respondents to the LFS Sample Size Ontario households Ontario economic families Economic family members aged 15 and over 12 787 12 787 25 418 Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 6 0 Data Collection Data collection for the Labour Force Survey LFS is carried out each month during the week following the LFS reference week The reference week is normally the week containing the 15 day ofthe month 6 1 Interviewing for the Labour Force Survey Statistics Canada interviewers are employees hired and trained to carry out the LFS and other household surveys Each month they contact the sampled dwellings to obtain the required labour force information Each interviewer contacts approximately 75 dwellings per month Dwellings new to the sample are usually contacted through a persona
24. he LFS The LFS weighting procedure is briefly described below 11 1 Weighting Procedures for the Labour Force Survey In the LFS the final weight attached to each record is the product of the following factors the basic weight the cluster sub weight the stabilization weight the balancing factor for non response and the province age sex and sub provincial area ratio adjustment factor Each is described below Basic Weight In a probability sample the sample design itself determines weights which must be used to produce unbiased estimates of population Each record must be weighted by the inverse of the probability of selecting the person to whom the record refers In the example of a 296 simple random sample this probability would be 0 02 for each person and the records must be weighted by 1 0 02 50 Due to the complex LFS design dwellings in different regions will have different basic weights Because all eligible individuals in a dwelling are interviewed directly or by proxy this probability is essentially the same as the probability with which the dwelling is selected Cluster Sub weight The cluster delineation is such that the number of dwellings in the sample increases very slightly with moderate growth in the housing stock Substantial growth can be tolerated in an isolated cluster before the additional sample represents a field collection problem However if growth takes place in more than one cluster in an interviewer assign
25. hey were coded as out of scope and were dropped from further processing When supplementary survey records do not match to host survey records they must be dropped since a weight cannot be derived for them Responses to income questions were examined for consistency between reporting of wage salary as a source of family income and the actual reporting of wage salary values for any member of the family Also cases in which families reported no income for 2008 were analyzed using socio demographic and labour information Due to a low number of cases with possible discrepancies the original responses were retained Very low as well very high incomes were also examined The impact of these values on key estimates such as the median household economic family income was determined to be minimal so no corrective action was taken 8 2 4 Non response A major source of non sampling errors in surveys is the effect of non response on the survey results The extent of non response varies from partial non response failure to answer just one or some questions to total non response Total non response occurred because the interviewer was either unable to contact the respondent no member of the household was able to provide the information or the respondent refused to participate in the survey Total non response was handled by adjusting the weight of households that responded to the survey to compensate for those that did not respond In most cases parti
26. ics Canada recommends not to release estimates of unacceptable quality However if the user chooses to do so then estimates should be flagged with the letter F or some similar identifier and the following warning should accompany the estimates Please be warned that these estimates flagged with the letter F do not meet Statistics Canada s quality standards Conclusions based on these data will be unreliable and most likely invalid Income Statistics Division 33 Ontario Material Deprivation Survey 2009 User Guide 10 0 Bootstrap Method for Variance In order to determine the quality of the estimate and to calculate the coefficient of variation CV the standard deviation must be calculated Confidence intervals also require the standard deviation of the estimate The OMDS uses a multi stage survey design and calibration which means that there is no simple formula that can be used to calculate variance estimates Therefore an approximate method was needed The Rao Wu bootstrap method is used because the sample design and calibration needs to be taken into account when calculating variance estimates The Rao Wu bootstrap method does this and with the use of the Bootvar program discussed in the next section is a method that is fairly easy for users The OMDS uses the Rao Wu bootstrap method described in the 1987 paper Resampling inference with complex survey data Journal of the American Statistical Association 83 2
27. ily immigrant status family sources of income and main source of income The total family income as well as the income of the major income earner were converted to ranges Capped variables The following variables were capped family size capped at 6 number of employed persons in the economic family number of unemployed persons in the economic family and number of family members in each of the three age groups The top income range was capped at 100 000 and the total weekly number of hours worked by all family members was capped at 80 hours Suppressions of values on selected records Dwelling type was suppressed and replaced with not stated on 599 records area size on 309 records and the ownership of dwelling variable on 177 records The suppressions of other variables main source of income number of unemployed number of employed highest level of education affected a much lower number of records Recoding of variables A small number of records had a demographic variable recoded to avoid potential identification of respondents resulting from an unusual combination of characteristics Income Statistics Division 21 Ontario Material Deprivation Survey 2009 User Guide 8 0 Data Quality 8 1 Response Rates The following table summarizes the response rates to the Labour Force Survey LFS and to the Ontario Material Deprivation Survey OMDS LFS LFS OMDS OMDS OMDS Overall LFS Selected Province Househo
28. l practice calls for researchers to provide users with some indication of the magnitude of this sampling error This section of the documentation outlines the measures of sampling error which Statistics Canada commonly uses and which it urges users producing estimates from this microdata file to use also The basis for measuring the potential size of sampling errors is the standard error of the estimates derived from survey results However because of the large variety of estimates that can be produced from a survey the standard error of an estimate is usually expressed relative to the estimate to which it pertains This resulting measure known as the coefficient of variation CV of an estimate is obtained by dividing the standard error of the estimate by the estimate itself and is expressed as a percentage of the estimate For example suppose that based upon the survey results one estimates that 5 9 of Ontario families reported that they can not afford to eat fresh fruit and vegetables every Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide day and this estimate is found to have a standard error of 0 003 Then the coefficient of variation of the estimate is calculated as 0 003 0 059 x 100 5 1 More information on the calculation of coefficients of variation can be found in Chapter 10 0 Income Statistics Division 27 Ontario Material Deprivation Survey 2009 User Guide 9 0
29. l visit using the computer assisted personal interview The interviewer first obtains socio demographic information for each household member and then obtains labour force information for all members aged 15 and over who are not members of the regular armed forces Provided there is a telephone in the dwelling and permission has been granted subsequent interviews are conducted by telephone This is done out of a centralized computer assisted telephone interviewing CATI unit where cases are assigned randomly to interviewers As a result approximately 85 of all households are interviewed by telephone In these subsequent monthly interviews the interviewer confirms the socio demographic information collected in the first month and collects the labour force information for the current month In each dwelling information about all household members is usually obtained from one knowledgeable household member Such proxy reporting which accounts for approximately 65 of the information collected is used to avoid the high cost and extended time requirements that would be involved in repeat visits or calls necessary to obtain information directly from each respondent If during the course of the six months that a dwelling normally remains in the sample an entire household moves out and is replaced by a new household information is obtained about the new household for the remainder of the six month period At the conclusion of the LFS m
30. lds Responding Response Responding Response Response Households Rate 96 Households Rate 92 Rate 96 Ontario 12 787 12 058 94 3 10 703 88 8 83 7 Note The OMDS overall response rate is based on all LFS household records The LFS responding households include respondents carried forward from the previous month The LFS response rate is the number of LFS responding households as a percentage the number of LFS selected households M The OMDS response rate is the number of OMDS responding households as a percentage of the number of LFS responding households zt The OMDS overall response rate is the number of OMDS responding households as a percentage of the number of LFS selected households 8 2 Survey Errors The estimates derived from this survey are based on a sample of households Somewhat different estimates might have been obtained if a complete census had been taken using the same questionnaire interviewers supervisors processing methods etc as those actually used in the survey The difference between the estimates obtained from the sample and those resulting from a complete count taken under similar conditions is called the sampling error of the estimate Errors which are not related to sampling may occur at almost every phase of a survey operation Interviewers may misunderstand instructions respondents may make errors in answering questions the answers may be incorrectly entered on the questi
31. le are person weights To use a family weight one has to select the weight of any family member For example when looking for an estimate of the number of families with no material deprivation one can look at the weighted derived variable MDNUM 0 where PRSNID 1 every family on the file includes a person identified as 1 Income Statistics Division 39 Ontario Material Deprivation Survey 2009 User Guide 12 0 Questionnaires 12 1 The Labour Force Survey Questionnaire The Labour Force Survey questionnaire LFS_QuestE pdf is used to collect information on the current and most recent labour market activity of all household members 15 years of age or older It includes questions on hours of work job tenure type of work reason for hours lost or absent job search undertaken availability for work and school attendance 12 2 The Ontario Material Deprivation Survey Questionnaire The Ontario Material Deprivation Survey OMDS questionnaire was used in March and April 2009 to collect the information for the supplementary survey The file OMDS2009 QuestE pdf contains the English questionnaire Income Statistics Division 41 Ontario Material Deprivation Survey 2009 User Guide 13 0 Record Layout with Univariate Frequencies See OMDS2009_PUMF_CdBk pdf for the record layout with univariate frequencies Income Statistics Division 43
32. le or more while rural areas are made up of areas not designated as urban or remote All urban areas are further subdivided into two types those using an apartment list frame and an area frame as well as those using only an area frame A detailed description of the LFS design is available in the Statistics Canada publication entitled Methodology of the Canadian Labour Force Survey Catalogue no 71 526 XPB Income Statistics Division 13 Ontario Material Deprivation Survey 2009 User Guide Approximately 1 of the LFS population is found in remote areas of provinces which are less accessible to LFS interviewers than other areas For administrative purposes this portion of the population is sampled separately through the remote area frame Some populations not congregated in places of 25 or more people are excluded from the sampling frame 5 2 3 Secondary Stratification In urban areas with sufficiently large numbers of apartment buildings the strata are subdivided into apartment frames and area frames The apartment list frame is a register maintained for the 18 largest cities across Canada The purpose of this is to ensure better representation of apartment dwellers in the sample as well as to minimize the effect of growth in clusters due to construction of new apartment buildings In the major cities the apartment strata are further stratified into low income strata and regular strata Where it is possible and or necessar
33. ly aware of the quality characteristics of these data First the number of respondents who contribute to the calculation of the estimate should be determined If this number is less than 30 the weighted estimate should be considered to be of unacceptable quality For weighted estimates based on sample sizes of 30 or more users should determine the coefficient of variation of the estimate and follow the guidelines below These quality level guidelines should be applied to rounded weighted estimates All estimates can be considered releasable However those of marginal or unacceptable quality level must be accompanied by a warning to caution subsequent users Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide Quality Level Guidelines Quality Level of Estimate Guidelines 1 Acceptable Estimates have a sample size of 30 or more and low coefficients of variation in the range of 0 0 to 16 5 No warning is required 2 Marginal Estimates have a sample size of 30 or more and high coefficients of variation in the range of 16 6 to 33 3 Estimates should be flagged with the letter E or some similar identifier They should be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimates Unacceptable Estimates have a sample size of less than 30 or very high coefficients of variation in excess of 33 3 Statist
34. m these dwellings LFS information is obtained for approximately 102 000 civilians aged 15 or over 5 4 Sample Rotation The LFS follows a rotating panel sample design in which households remain in the sample for six consecutive months The total sample consists of six representative sub samples or panels and each month a panel is replaced after completing its six month stay in the survey Outgoing households are replaced by households in the same or a similar area This results in a five sixths month to month sample overlap which makes the design efficient for estimating month to month changes The rotation after six months prevents undue respondent burden for households that are selected for the survey Because of the rotation group feature it is possible to readily conduct supplementary surveys using the LFS design but employing less than the full size sample 5 5 Modifications to the Labour Force Survey Design for the Ontario Material Deprivation Survey The OMDS used two of the six rotation groups in the March LFS sample and three rotation groups in the April LFS sample For the OMDS coverage was at the economic family level Unlike the LFS where information is collected for all eligible household members the OMDS collected information about an economic family and its members If the LFS household consisted Income Statistics Division 15 Ontario Material Deprivation Survey 2009 User Guide of more than one economic family one o
35. material deprivation number of types of material deprivation experienced due to the lack of affordability was derived from the set of material deprivation questions Total family income before tax was derived by adding incomes of all family members The LICO status was derived by comparison of the total family income with the low income cut off values published by Statistics Canada 7 6 Weighting The principle behind estimation in a probability sample such as the LFS is that each person in the sample represents besides himself or herself several other persons not in the sample For example in a simple random 2 sample of the population each person in the sample represents 50 persons in the population The weighting phase is a step which calculates for each record what this number is This weight appears on the microdata file and must be used to derive meaningful estimates from the survey For example if the number of Ontario families experiencing one or more types of material deprivation is to be estimated it would be done by selecting the records referring to those families in the sample with that characteristic and summing the weights entered on those records Details of the method used to calculate these weights are presented in Chapter 11 0 Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 7 7 Suppression of Confidential Information It should be noted that the Public Use Mic
36. ment the cumulative effect of all increases may create a workload problem In clusters where substantial growth has taken place sub sampling is used as a means of keeping interviewer assignments manageable The cluster sub weight represents the inverse of this sub sampling ratio in clusters where sub sampling has occurred Stabilization Weight Sample stabilization is also used to address problems with sample size growth Cluster sub sampling addressed isolated growth in relatively small areas whereas sample stabilization accommodates the slow sample growth over time that is the result of a fixed sampling rate along with a general increase in the size of the population Sample stabilization is the random dropping of dwellings from the sample in order to maintain the sample size at its desired level The basic weight is adjusted by the ratio of the sample size based on the fixed sampling rate to the desired sample size This adjustment factor is known as the stabilization weight The adjustment is done within stabilization areas defined as dwellings belonging to the same employment insurance economic region and the same rotation group Non response For certain types of non response i e household temporarily absent refusal data from a previous month s interview with the household if any is brought forward and used as the current month s data for the household In other cases non response is compensated for by proportionally increasing the w
37. n response to the Labour Force 17 6 4 Data Collection Modifications for the Ontario Material Deprivation Survey 18 6 5 Non response to the Ontario Material Deprivation Survey 18 DECR CIS rine c 19 7 1 Data Capture ERE 19 7 2 Editing esee deine datu pei eiae tani See eee 19 7 3 Coding Open ended Questions 19 7 4 Imputation 19 7 5 Creation of Derived Variables 20 7 6 Weight Gata me Ree terrea re re va p ot reete lH 20 Data Qualily A 23 8 1 Response R les ur une awl epe a er bed o a e o a erae 23 8 2 NAME 23 821 A eee He ete le ite ia ie 23 8 2 2 Data Collection ci eame eis 24 8 2 8 Data 55 24 8 2 4 MNori response ann sense are nein 24 8 2 5 Measurement of Sampling Error sse 26 Income Statistics Division 3 9 0 10 0 12 0 13 0 Ontario Material Deprivation Survey 2009 User Guide Guidelines for Tabulation Analysis and Release esent 29 9 1 PRounding G ldelinesi usina 29 9 2 Sample Weighting Guidelines for 29 9 3 Definitions of Types of Estimates Categorical and 30 9 3 1 Categorical
38. not self weighting When producing simple estimates including the production of ordinary statistical tables users must apply the proper survey weights If proper weights are not used the estimates derived from the microdata files cannot be considered to be representative of the survey population and will not correspond to those produced by Statistics Canada Income Statistics Division 29 30 Ontario Material Deprivation Survey 2009 User Guide Users should also note that some software packages may not allow the generation of estimates that exactly match those available from Statistics Canada because of their treatment of the weight field 9 3 Definitions of Types of Estimates Categorical and Quantitative Before discussing how the OMDS data can be tabulated and analyzed it is useful to describe the two main types of point estimates of population characteristics which can be generated from the microdata file for the OMDS 9 39 1 Categorical Estimates Categorical estimates are estimates of the number or percentage of the surveyed population possessing certain characteristics or falling into some defined category The number of Ontario families who experienced at least one material deprivation or the percentage of children below age 15 who lived in Ontario families experiencing at least one deprivation are examples of such estimates An estimate of the number of persons possessing a certain characteristic may also be referred to
39. on Income Statistics Division Ontario Material Deprivation Survey 2009 User Guide 7 0 Data Processing The main output of the Ontario Material Deprivation Survey OMDS is a clean microdata file This chapter presents a brief summary of the processing steps involved in producing this file 7 1 Data Capture Responses to survey questions are captured directly by the interviewer at the time of the interview using a computerized questionnaire The computerized questionnaire reduces processing time and costs associated with data entry transcription errors and data transmission The response data are encrypted to ensure confidentiality and sent via modem to the appropriate Statistics Canada Regional Office From there they are transmitted over a secure line to Ottawa for further processing Some editing is done directly at the time of the interview Where the information entered is out of range too large or small of expected values or inconsistent with the previous entries the interviewer is prompted through message screens on the computer to modify the information However for some questions interviewers have the option of bypassing the edits and of skipping questions if the respondent does not know the answer or refuses to answer Therefore the response data are subjected to further edit and imputation processes once they arrive in head office 7 2 Editing The first stage of survey processing undertaken at head office wa
40. onnaire and errors may be introduced in the processing and tabulation of the data These are all examples of non sampling errors Over a large number of observations randomly occurring errors will have little effect on estimates derived from the survey However errors occurring systematically will contribute to biases in the survey estimates Considerable time and effort were taken to reduce non sampling errors in the survey Quality assurance measures were implemented at each step of the data collection and processing cycle to monitor the quality of the data These measures include the use of highly skilled interviewers extensive training of interviewers with respect to the survey procedures and questionnaire observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions procedures to ensure that data capture errors were minimized and coding and edit quality checks to verify the processing logic 8 2 1 The Frame Since the OMDS was a supplement to the LFS the frame used was the LFS frame Any non response to the LFS had an impact on the OMDS frame The quality of the sampling Income Statistics Division 23 24 Ontario Material Deprivation Survey 2009 User Guide variables in the frame was very high The OMDS sample consisted of Ontario economic families in five LFS rotation groups The criteria used for the OMDS selection such as a rotation group were not missing for any LFS records N
41. onthly interviews interviewers introduce the supplementary survey if any to be administered to some or all household members that month 6 2 Supervision and Quality Control All LFS interviewers are under the supervision of a staff of senior interviewers who are responsible for ensuring that interviewers are familiar with the concepts and procedures of the LFS and it s many supplementary surveys and also for periodically monitoring their interviewers and reviewing their completed documents The senior interviewers are in turn under the supervision of the LFS program managers located in each of the Statistics Canada regional offices 6 3 Non response to the Labour Force Survey Interviewers are instructed to make all reasonable attempts to obtain LFS interviews with members of eligible households For individuals who at first refuse to participate in the LFS a letter is sent from the Regional Office to the dwelling address stressing the importance of the survey and the household s cooperation This is followed by a second call or visit from the interviewer For cases in which the timing of the interviewer s call or visit is inconvenient an appointment is arranged to call back at a more convenient time For cases in which there is no one home numerous call backs are made Under no circumstances are sampled dwellings replaced by other dwellings for reasons of non response Income Statistics Division 17 Ontario Material Deprivation Sur
42. ote that the LFS frame excludes about 2 of all households in the 10 provinces of Canada Therefore the OMDS frame also excludes a similar proportion of Ontario households It is unlikely that this exclusion introduces any significant bias into the survey data 8 2 2 Data Collection Interviewer training consisted of reading the OMDS Interviewer s Manual practicing with the OMDS training cases on the computer and discussing any questions with senior interviewers before the start of the survey A description of the background and objectives of the survey was provided as well as a glossary of terms and a set of questions and answers Interviewers collected the OMDS information after the LFS information was collected The collection period ran from March 22 to April 6 2009 and from April 19 to May 4 2009 In general interviews went smoothly and quickly with an average interview time of slightly less than 5 minutes 8 2 3 Data Processing Data processing of the OMDS was done in a number of steps including clean up pre edit verification coding flow editing imputation and estimation At each step a picture of the output files was taken and an easy verification was be made comparing files at the current and previous step This greatly improved the data processing stage During processing of the data 10 OMDS household economic family level records as well 4 records at the person level did not match to corresponding records in the LFS Thus t
43. porary nature such as because of own illness or disability personal or family responsibilities because they already have a job to start in the near future or because of vacation prior to 1997 those on vacation were not considered available were full time students seeking part time work who also met condition i above Full time students currently attending school and looking for full time work are not considered to be available for work during the reference week Income Statistics Division 11 Ontario Material Deprivation Survey 2009 User Guide Industry and Occupation The Labour Force Survey provides information about the occupation and industry attachment of employed and unemployed persons and of persons not in the labour force who have held a job in the past 12 months Since 1997 these statistics have been based on the North American Industry Classification System NAICS and the Standard Occupational Classification SOC 91 Prior to 1997 the 1980 Standard Industrial Classification and the 1980 Standard Occupational Classification were used Reference Week The entire calendar week from Sunday to Saturday covered by the Labour Force Survey each month It is usually the week containing the 15 day of the month The interviews are conducted during the following week called the Survey Week and the labour force status determined is that of the reference week Full time Employment Full time employment consists of persons
44. rodata Files PUMF may differ from the survey master files held by Statistics Canada These differences usually are the result of actions taken to protect the anonymity of individual survey respondents The most common actions are reduction of the number of variables grouping values into wider categories and coding specific values into the not stated category Users requiring access to information excluded from the microdata files may purchase custom tabulations Estimates generated will be released to the user subject to meeting the guidelines for analysis and release outlined in Chapter 9 0 of this document Differences between the OMDS master file and the public use file File structure Unlike the master file the OMDS public use file is designed as a family level file The variables that originate from the OMDS supplement material deprivation and family income are at the family level on both files while some of the LFS variables in order to be included on the OMDS PUMF had to be derived as family not person characteristics These are number of family members in each of three broad age groups the highest education level of the major income earner and immigrant status of the major income earner Several LFS variables describing the specifics of employment are not included on the public use file Grouped variables The number of categories was reduced in the following variables area size dwelling type type of economic fam
45. s the replacement of any out of range values on the data file with blanks This process was designed to make further editing easier The first type of error treated was errors in questionnaire flow where questions which did not apply to the respondent and should therefore not have been answered were found to contain answers In this case a computer edit automatically eliminated superfluous data by following the flow of the questionnaire implied by answers to previous and in some cases subsequent questions The second type of error treated involved a lack of information in questions which should have been answered For this type of error a non response or not stated code was assigned to the item 7 3 Coding of Open ended Questions There were no open ended questions in the OMDS 7 4 Imputation Imputation is the process that supplies valid values for those variables that have been identified for a change either because of invalid information or because of missing information The new values are supplied in such a way as to preserve the underlying structure of the data and to ensure that the resulting records will pass all required edits In other words the objective is not to reproduce the true microdata values but rather to establish internally consistent data records that yield good aggregate estimates Income Statistics Division 19 Ontario Material Deprivation Survey 2009 User Guide We can distinguish between three
46. statistical tables are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units using normal rounding Averages proportions rates and percentages are to be computed from unrounded components i e numerators and or denominators and then are to be rounded themselves to one decimal using normal rounding In normal rounding to a single digit if the final or only digit to be dropped is O to 4 the last digit to be retained is not changed If the first or only digit to be dropped is 5 to 9 the last digit to be retained is increased by 1 Sums and differences of aggregates or ratios are to be derived from their corresponding unrounded components and then are to be rounded themselves to the nearest 100 units or the nearest one decimal using normal rounding In instances where due to technical or other limitations a rounding technique other than normal rounding is used resulting in estimates to be published or otherwise released which differ from corresponding estimates published by Statistics Canada users are urged to note the reason for such differences in the publication or release document s Under no circumstances are unrounded estimates to be published or otherwise released by users Unrounded estimates imply greater precision than actually exists Sample Weighting Guidelines for Tabulation The sample design used for the Ontario Material Deprivation Survey OMDS was
47. ster Have appropriate clothes for job interviews 10 614 0 8 88 0 83 0 Able to get around your community either by having a car or by taking the bus or an 10 691 0 1 88 7 83 6 equivalent mode of transportation Able to have friends or family over for a 10 674 03 88 5 83 5 meal at least once a month House or apartment free of pests such as 10 670 03 88 5 83 4 cockroaches Able to buy some small gifts for family or 10 678 02 88 6 83 5 friends at least once a year Have a hobby or leisure activity 10 684 0 2 88 6 83 6 The OMDS item response rate combined with the OMDS response rate of 88 896 The OMDS item response rate combined with the OMDS response rate of 88 896 and the LFS response rate of 94 396 All imputations involved donors that were selected using a score function For each item non response or partial non response records also called recipient records we compared certain characteristics to characteristics from all the donors When the characteristics were the same between a donor and the recipient a value was added to the score of that donor The donor with the highest score was deemed the closest Income Statistics Division 25 Ontario Material Deprivation Survey 2009 User Guide 26 donor and was chosen to fill in missing pieces of information of the non respondents If there was more than one donor with the highest score a random selection occurred The pool of donors was made up in such a way that th
48. the final weights of records having the characteristic of interest for the numerator X b summing the final weights of records having the characteristic of interest for the denominator Y then C dividing estimate a by estimate b X 9 3 4 Tabulation of Quantitative Estimates Estimates of quantities can be obtained from the microdata file by multiplying the value of the variable of interest by the final weight for each record then summing this quantity over all records of interest For example to obtain an estimate of the total number of deprivations experienced by Ontario families multiply the value reported in derived variable MDNUM number of types of deprivations experienced by the final weight for the record then sum this value over all records with MDNUM gt 0 at least one deprivation reported To obtain a weighted average of the form the numerator X is calculated as for a quantitative estimate and the denominator Y is calculated as for a categorical estimate For example to estimate the average number of deprivations experienced by Ontario families who experienced at least one deprivation a estimate the total number of deprivations X as described above b estimate the number of families Y in this category by summing the final weights of all records with MDNUM gt 0 then C divide estimate a by estimate b X Y 9 4 Guidelines for Statistical Analysis
49. vey 2009 User Guide Each month after all attempts to obtain interviews have been made a small number of non responding households remain For households non responding to the LFS and for which LFS information was obtained in the previous month this information is brought forward and used as the current month s LFS information No supplementary survey information is collected for these households 6 4 Data Collection Modifications for the Ontario Material Deprivation Survey Upon completion of the Labour Force Survey interview the interviewer asked to speak to the most knowledgeable person to participate in the OMDS interview If this person was not available the interviewer arranged for a convenient time to call back The collection period was extended by one week following the LFS week to allow interviewers time to contact these individuals The OMDS respondent was asked a set of material deprivation questions as well as questions on sources of family income and personal income of family members aged 15 and over In order to reduce response burden income information was collected for up to and including four persons only within one economic family 6 5 Non response to the Ontario Material Deprivation Survey The next stage of data collection for households responding to the LFS was to administer the OMDS In the event that the supplementary survey was met with a refusal a senior interviewer made another call to try to gain participati
50. y the urban area frame is further stratified into regular strata high income strata and low population density strata Most urban areas fall into the regular urban strata which in fact cover the majority of Canada s population High income strata are found in major urban areas while low density urban strata consist of small towns that are geographically scattered In rural areas the population density can vary greatly from relatively high population density areas to low population density areas resulting in the formation of strata that reflect these variations The different stratification strategies for rural areas were based not only on concentration of population but also on cost efficiency and interviewer constraints In each province remote settlements are sampled proportional to the number of dwellings in the settlement with no further stratification taking place Dwellings are selected using systematic sampling in each of the places sampled 5 2 4 Cluster Delineation and Selection Households in final strata are not selected directly Instead each stratum is divided into clusters and then a sample of clusters is selected within the stratum Dwellings are then sampled from selected clusters Different methods are used to define the clusters depending on the type of stratum Within each urban stratum in the urban area frame a number of geographically contiguous groups of dwellings or clusters are formed based upon 1991 Census

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