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Microdata User Guide CANADIAN TOBACCO USE MONITORING

1. 47 11 2 Weighting Procedures for the Household File sse 48 11 3 Weighting Procedures for the Person File ssssssseeeeeeeennnennn 49 Questionnaite eR v 51 Record Layouts with Univariate Frequencies eeeeeeeeeeeereeenen nennen nnn 53 13 1 Record Layout with Univariate Frequencies Household File 53 13 2 Record Layout with Univariate Frequencies Person 53 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 1 0 Introduction The Canadian Tobacco Use Monitoring Survey CTUMS was conducted by Statistics Canada from July to December 2004 with the cooperation and support of Health Canada This manual has been produced to facilitate the manipulation of the microdata file of the survey results Any questions about the data set or its use should be directed to Statistics Canada Client Services Special Surveys Division Telephone 613 951 3321 or call toll free 1 800 461 9050 Fax 613 951 4527 E mail ssd statcan ca Elizabeth Majewski Special Surveys Division 2nd floor Main Building Tunney s Pasture Ottawa Ontario K1A 0T6 Telephone 613 951 4584 Fax 613 951 0562 E mail elizabeth majewski statcan ca Health Canada Murray Kaiserman Office of Research Surveillance and
2. 1205 1 097 910 Saskatchewan f 1303 1 188 908 Alberta 1277 oo British Columbia 110 1 087 886 mm me m Special Surveys Division 23 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Person Response Rate by Survey Month Total Persons Total Persons Person Response survey Month Selected Responding Rate 96 2 164 1880 872 2 214 2002 904 September 2065 1 860 901 October 2118 1855 876 ef November 2177 1947 894 Decembr 19 894 sm ne m Target Number of Respondents and Person Response Rate by Age Group Total Persons Total Persons Person Response Selected Responding Rate 96 15 to 19 3 280 2 899 Age Group 20 to 24 2 896 2 496 6 693 6 061 906 Overall Response Rate by Province Province Household Person Overall Response Rate Response Rate Response Rate Newfoundland and Labrador 91 2 87 2 79 5 Prince Edward Island 88 4 90 5 80 0 Nova Scotia 89 8 89 0 79 9 New Brunswick 87 9 88 9 78 1 Quebec 78 8 87 0 68 6 Ontario 80 8 86 3 69 8 Manitoba 83 0 91 0 75 5 Saskatchewan 86 8 90 8 78 8 Alberta 83 8 91 0 76 2 British Columbia 81 7 88 6 72 4 Canada 85 0 89 0 75 7 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004
3. Age Information about the respondent s age is obtained from two sources from a household respondent who provided the ages of all the household members roster age and later at the beginning of the interview with the selected person directly from the individual respondent who is asked to state his her age The DVAGE variable is the age provided by the selected respondent or when it is not available e g refused the roster age is used Special Surveys Division 11 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 5 0 Survey Methodology The Canadian Tobacco Use Monitoring Survey was administered between July 2nd and December 30th 2004 as a Random Digit Dialing RDD survey a technique whereby telephone numbers are generated randomly by computer Interviewing was conducted over the telephone 5 1 Population Coverage The target population for the Canadian Tobacco Use Monitoring Survey was all persons 15 years of age and over living in Canada with the following two exceptions 1 residents ofthe Yukon Northwest Territories and Nunavut and 2 full time residents of institutions Because the survey was conducted using a sample of telephone numbers households and thus persons living in households that do not have telephones were excluded from the sample population People without telephones account for less than 3 of the target population However the survey estimates have been weighted to include persons w
4. User Guide 8 3 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 questionnaire 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 was made 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 extensive training of interviewers with respect to the survey procedures and computer assisted telephone interviewing CATI application
5. Microdata User Guide CANADIAN TOBACCO USE MONITORING SURVEY CYCLE 2 JULY DECEMBER 2004 Pel e eus Canada Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Table of Contents 1 0 2 0 3 0 4 0 5 0 6 0 7 0 8 0 9 0 Special Surveys Division Introduction ea 5 Iri onde 7 A A c 9 Concepts and 11 TAA MethOdOlOGY oon sists T oO carai paaie a anaana Naat 13 5 1 Population Goverage 4 vv avin de aa rn ann 13 5 2 urs are rl ha gain ae 13 5 3 Sample Design and Allocation u 2200444400nnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnannnnnn 13 5 4 Sample Selection h P 14 Data Collection idas 17 6 1 Questionnaire Design e tree tidad eta 17 6 2 Data Collection and Edltirig eira a ee cate ee rette te bete 17 Data Processihg E ia 19 7 1 Data Capture an eter reads 19 7 2 EditiNG 19 7 3 Creation of Derived aeaea aa a amaaa 19 7 4 WIG IMIG ee 19 7 5 Suppression of Confidential Information ss4s40u4r200nnnnnennnnnnnnnnnnnnnnnnnnennnnnnnnnn 20 Data Quality eL ica 21 8 1 Household Response Rates July to De
6. 15 19 1 38 276 822 960 20 24 1 35 253 828 716 25 1 32 601 8 408 219 Manitoba All 1 68 1 097 921 190 15 19 1 33 274 84 268 20 24 1 39 240 80 687 25 1 30 583 756 236 Saskatchewan All 1 54 1 183 788 904 15 19 1 36 293 76 253 20 24 1 41 261 71 345 25 1 23 629 641 306 Alberta All 1 54 1 277 2 571 429 15 19 1 43 310 231 629 20 24 1 42 267 250 643 25 1 22 700 2 089 157 British Columbia All 1 56 1 037 3 496 729 15 19 1 27 261 275 960 20 24 1 30 198 294 260 25 1 19 578 2 926 509 Canada All 3 94 11 456 26 003 758 15 19 3 14 2 902 2 105 221 20 24 2 97 2 475 2 187 488 254 2 95 6 080 21 711 049 36 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide All coefficients of variation in the Approximate Sampling Variability Tables are approximate and therefore unofficial Estimates of actual variance for specific variables may be obtained from Statistics Canada on a cost recovery basis Users of the 2004 CTUMS interested in calculating actual variance estimates may obtain upon request free of charge bootstrap weights with programs that compute variance estimates for various statistics Since the approximate CV is conservative the use of actual variance estimates may cause the estimate to be switched from one quality level to another For instance a marginal estimates could become acceptable based on the exact CV calculation Remember If the number of observations on which an estimate is based
7. 0 2 9 2 8 2 5 2 0 4000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 2 8 2 7 2 6 25 2 4 2 2 1 7 5000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 2 5 2 4 2 3 2 2 2 2 2 0 1 5 6000 kk kkk kkk kkk kkk k Hekk kkk k Hekk kek k Fekk kkk k k ekk k kk k kkk kk kkk 22 21 21 20 1 8 1 4 7000 kkkkkkkk kkk kkk kk kkk kkk kk kkk kkk kk kkk kkk kk kkk kk kkk kkkkkkkk 2 0 1 9 1 8 1 7 1 3 8000 kkkkkkkk kkk kkk kk kkkkkkkk kkk k kkk kkk kkk kk 1 8 1 7 1 6 1 2 9000 kkkkkkkk kkk kkk kk kkk k kkk k kkk kkk kk kkk kkk k kkk kkk kk kkkkkkkk kkkkkkkk kkk kkk kk kkkkkkkk 1 6 1 5 1 1 10000 kikki kkk kkk kkk kk kkk kkk kk kkkkkkkk kkk k kkk kkk kkk kk kkkkkkkk 1 5 1 4 1 1 12500 kkkkkkkk kkkkkkkk kkk kkk kk 1 2 1 0 15000 kkkkkkkk kkk kkk kk kkk kkk k kkk kkk kk kkk kk kk kkk kkk kk kkkkkkkk kkk kkkk kkk kkk kk kkkkkkkk kkk kkk kk kkk kkk kk 0 9 NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION Special Surveys Division 39 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 2 The estimated aggregate 5 414 335 does not appear in the left hand column the Numerator of Percentage column so it is necessary to use the figure closest to it namely 5 000 000 3 The coefficient of variation for an estimated aggregate is found by referring to the first non asterisk entry on that row n
8. 8 88 2 80 5 62 4 98 6 98 1 97 6 96 1 93 6 90 9 88 2 85 4 82 5 79 5 76 4 69 7 54 0 88 2 87 8 87 3 86 0 83 7 81 3 78 9 76 4 73 8 71 1 68 3 62 4 48 3 qb eem 22 7 22 5 22 2 21 6 21 0 20 4 19 7 19 1 18 4 17 6 16 1 12 5 80 es 21 9 21 8 21 5 20 9 20 3 19 7 19 1 18 5 17 8 171 15 6 12 1 gb eem 21 8 21 2 20 9 20 3 19 7 19 1 18 5 17 9 17 2 16 6 15 1 11 7 90 ee 20 7 20 6 20 3 19 7 19 2 18 6 18 0 17 4 16 8 16 1 14 7 11 4 20 1 20 0 19 7 19 2 18 7 18 1 17 5 16 9 16 3 15 7 14 3 111 100 19 6 19 5 19 2 18 7 18 2 17 6 17 1 16 5 15 9 15 3 13 9 10 8 125 EE 17 6 17 5 17 2 16 7 16 3 15 8 15 3 14 8 14 2 13 7 12 5 9 7 150 16 0 15 9 15 7 15 3 14 8 14 4 13 9 13 5 13 0 12 5 11 4 8 8 200 e 13 9 13 8 13 6 13 2 12 9 12 5 12 1 11 7 11 2 10 8 9 9 7 6 250 e 12 4 12 4 12 2 11 8 11 5 11 2 10 8 10 4 10 1 9 7 8 8 6 8 300 EEES gutem 11 3 11 1 10 8 10 5 10 2 9 9 9 5 9 2 8 8 8 1 6 2 350 orum 10 4 10 3 10 0 9 7 9 4 9 1 8 8 8 5 8 2 7 5 5 8 400 Hr 9 8 9 6 9 4 9 1 8 8 8 5 8 3 8 0 7 6 7 0 5 4 450 NEUEN TEDAN 9 2 9 1 8 8 8 6 8 3 8 1 7 8 7 5 7 2 6 6 5 1 en 8 7 8 6 8 4 8 1 7 9 7 6 7 4 7 1 6 8 6 2 4 8 TOO EAN ROTE 7 0 6 8 6 6 6 4 6 2 6 0 5 8 5 6 5 1 3 9 1000 ERES EES ATASE 6 1 5 9 5 8 5 6 5 4 5 2 5 0 4 8 4 4 3 4 1500 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 4 8 4 7 4 6 4 4 4 3 4 1 3 9 3 6 2 8 2000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 4 2 4 1 3 9 3 8 3 7 3 6 3 4 3 1 24 3000 kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk 3 3 3 2 3 1 3
9. Evaluation Tobacco Control Programme Healthy Environments amp Consumer Safety Branch MacDonald Building AL 3507C 123 Slater Street Room A723 Ottawa Ontario KIA OK9 Telephone 613 954 5851 Fax 613 954 2292 E mail Murray Kaiserman hc sc gc ca Judy Snider Office of Research Surveillance and Evaluation Tobacco Control Programme Healthy Environments amp Consumer Safety Branch MacDonald Building AL 3507C 123 Slater Street Room A716 Ottawa Ontario KIA OK9 Telephone 613 957 0697 Fax 613 954 2292 E mail Judy Snider hc sc gc ca Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 2 0 Background Statistics Canada has conducted smoking surveys on an ad hoc basis on behalf of Health Canada since the 1960s These surveys have been done as supplements to the Canadian Labour Force Survey and as random digit dialing telephone surveys In February 1994 a change in legislation was passed which allowed a reduction in cigarette taxes Since there was no survey data from immediately before this legislative change it was difficult for Health Canada or other interested analysts to measure exactly the impact of the change As Health Canada wants to be able to monitor the consequences of legislative changes and anti smoking policies on smoking behaviour the Canadian Tobacco Use Monitoring Survey CTUMS was designed to provide Health Canada and its partners stakeholders with
10. New Brunswick bea me me e _ 22 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Household Response Rate by Survey Month Number of Total Number of Household Survey Month Responding Households Response Rate 96 Households 8 2 Person Response Rates July to December 2004 A person respondent has the following characteristics The telephone number of the selected person belonged to a responding household The household roster was completed with no individual age refusals selected person was 15 years of age or older at the time of the interview confirmed with the selected person The selected person answered the key questions on smoking habits at minimum There were 14 631 households in which household data was collected but nobody was selected to continue with the CTUMS See Section 5 4 Sample Selection for more information Of the remaining households 9 579 had one person selected while 1 645 had two people selected The refusal rate at the person level was 2 996 Person Response Rate by Province Total Persons Total Persons Person Response Selected Responding Rate 96 Newfoundland andLabrador 1233 105 872 Prince Edward Island 122 11242 sos Nova Scotia o 1 889 f New Brunswick Ya 1100 889 Province Quebec w P a 870 Ontario 1309 1130 863 Manitoba
11. age group is retained for only a proportion of the cases Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 6 If some household members are 20 to 24 and the rest are 25 and over then two people are selected at random one from each age group however the person selected from the 25 and over age group is retained for only a proportion of the cases 7 Ifallthree age groups are represented in the household then two age groups are selected at random and then rule 4 5 or 6 applies Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 6 0 Data Collection 6 1 Questionnaire Design The questionnaire design for this survey borrows heavily from the 1994 Survey on Smoking in Canada Some questions have been added for consistency with international surveys which use the concept of smoking behaviour in the last 30 days The questionnaire used for the Canadian Tobacco Use Monitoring Survey during Cycle 2 of 2004 contains several questions that were not asked in Cycle 1 of 2004 The new questions refer to purchases of cigarettes and efforts made to buy cigarettes at a lower price For the Cycle 1 2004 data collection a new computer application was introduced Because of this change the questionnaire had to be divided into thematic sections and questions were numbered within each section For users who want to make comparisons with earlier cycles
12. coefficients of variation in Chapter 10 0 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 9 0 Guidelines for Tabulation Analysis and Release This chapter of the documentation outlines the guidelines to be adhered to by users tabulating analysing 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 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 0 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
13. difference between the two estimates at the 0 05 level of significance 10 4 Coefficient of Variation for Quantitative Estimates For quantitative estimates special tables would have to be produced to determine their sampling error Since most of the variables for the Canadian Tobacco Use Monitoring Survey are primarily categorical in nature this has not been done As a general rule however the coefficient of variation of a quantitative total will be larger than the coefficient of variation of the corresponding category estimate i e the estimate of the number of persons contributing to the quantitative estimate If the corresponding category estimate is not releasable the quantitative estimate will not be either For example the coefficient of variation of the total number of cigarettes smoked on Saturday would be greater than the coefficient of variation of the corresponding proportion of current smokers Hence if the coefficient of variation of the proportion is unacceptable making the proportion not releasable then the coefficient of variation of the corresponding quantitative estimate will also be unacceptable making the quantitative estimate not releasable Coefficients of variation of such estimates can be derived as required for a specific estimate using a technique known as pseudo replication This involves dividing the records on the microdata files into subgroups or replicates and determining the variation in the estimate f
14. following formula to convert to a confidence interval CI x N X where is the determined coefficient of variation of X t 1 if a 68 confidence interval is desired t 1 6 if a 90 confidence interval is desired t 2 if a 95 confidence interval is desired t 2 6 if a 99 confidence interval is desired Note Release guidelines which apply to the estimate also apply to the confidence interval For example if the estimate is not releasable then the confidence interval is not releasable either Special Surveys Division 43 44 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence Limits A 95 confidence interval for the estimated proportion of men who currently smoke from Example 2 Section 10 1 1 would be calculated as follows A X 23 0 or expressed as a proportion 0 230 t 2 A 3 1 0 031 expressed as a proportion is the coefficient of variation of this estimate as determined from the tables 0 230 2 0 230 0 031 0 230 2 0 230 0 031 0 230 0 014 0 230 0 014 0 216 0 244 With 95 confidence it can be said that between 21 6 and 24 4 of men currently smoke 10 3 How to Use the Coefficient of Variation Tables to Do a T test Standard errors may also be used to perform hypothesis testing a procedure for distinguishin
15. lt 12 000 11 000 to 43 000 Alberta 9 500 to lt 33 500 11 500 to lt 41 000 British Columbia 11 500_to lt 42 000 16 500 lt 57 000 _ 324 500 amp over 80 500 to lt 324 500 under 80 500 5 19 80 500 amp over 20 500 to lt 80 500 under 20 500 20 24 92 500 amp over 23 500 to lt 92 500 under 23 500 380 000 amp over 94 500 to lt 380 000 under 94 500 Special Surveys Division 33 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 10 0 Approximate Sampling Variability Tables In order to supply coefficients of variation CV which would be applicable to a wide variety of categorical estimates produced from this microdata file and which could be readily accessed by the user a set of Approximate Sampling Variability Tables has been produced These CV tables allow the user to obtain an approximate coefficient of variation based on the size of the estimate calculated from the survey data The coefficients of variation are derived using the variance formula for simple random sampling and incorporating a factor which reflects the multi stage clustered nature of the sample design This factor known as the design effect was determined by first calculating design effects for a wide range of characteristics and then choosing from among these a conservative value usually the 75 percentile to be used in the CV tables which would then apply to the entire set of characteristics The ta
16. the new record layout is accompanied by a concordance table Specifications for valid ranges and inter question consistency were incorporated into the computer assisted telephone interviewing CATI application to the extent feasible Additional consistency edits were done during the data processing phase 6 2 Data Collection and Editing The interviews were conducted every month from July through December 2004 Data were collected using computer assisted telephone interviewing The CATI system has a number of generic modules which can be quickly adapted to most types of surveys A front end module contains a set of standard response codes for dealing with all possible call outcomes as well as the associated scripts to be read by the interviewers A standard approach set up for introducing the agency the name and purpose of the survey the survey sponsors how the survey results will be used and the duration of the interview was used We explained to respondents how they were selected for the survey that their participation in the survey is voluntary and that their information will remain strictly confidential Help screens were provided to the interviewers to assist them in answering questions that are commonly asked by respondents The CATI application ensured that only valid question responses were entered and that all the correct flows were followed Edits were built into the application to check the consistency of responses identify an
17. two 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 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 0 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 documeni s Under no circumstances are unrounded estimates to be published or otherwise released by users Unrounded estimates imply greater precision than actu
18. 2 For Cycle 1 and Cycle 2 population totals by province sex and the following age groups 15 to 19 20 to 24 25 to 34 35 to 44 45 to 54 55 to 64 and 65 and over These totals were averaged over the survey period For the Annual Summary population totals by province sex and the following age groups 15 to 19 20 to 24 25 to 29 30 to 34 35 to 39 40 to 44 45 to 49 50 to 54 55 to 59 60 to 64 65 to 69 and 70 and over These totals were averaged over the survey period The method called generalized regression GREG estimation was used to modify the weights to ensure that the survey estimates agreed with the external totals simultaneously along the two dimensions The person weights obtained after this step were considered final and appear on the person microdata file Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 12 0 Questionnaire Refer to CTUMS2004 C2 QuestE pdf for the English questionnaire used in Cycle 2 of 2004 Special Surveys Division 51 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 13 0 Record Layouts with Univariate Frequencies 13 1 Record Layout with Univariate Frequencies Household File Refer to CTUMS2004_C2_HH_CdBk pdf for the record layout with univariate counts for the Household file for Cycle2 of 2004 13 2 Record Layout with Univariate Frequencies Person File Refer to CTUMS2004_C2_PR_CdBk pdf for the record la
19. 64 3 62 5 60 6 58 7 56 7 54 6 52 5 47 9 37 1 21 4 ovas 55 0 54 8 53 9 52 5 51 0 49 5 47 9 46 3 44 6 42 9 39 1 30 3 17 5 47 7 47 4 46 7 45 5 44 2 42 9 41 5 40 1 38 6 37 1 33 9 26 2 15 2 42 6 42 4 41 8 40 7 39 5 38 3 37 1 35 9 34 6 33 2 30 3 23 5 13 6 ee 38 9 38 7 38 1 37 1 36 1 35 0 33 9 32 7 31 5 30 3 27 7 21 4 12 4 KR RARA rk 96 93 9 1 8 8 85 82 79 76 70 54 num 9 3 9 1 8 8 8 6 8 3 8 0 7 7 7 4 6 8 5 2 Pd 8 1 79 77 74 72 69 66 61 47 150 Hr serien en nen 74 72 70 68 65 63 61 5 5 43 200 cn ee 6 4 6 2 6 1 5 9 5 7 5 5 5 2 48 3 7 DN RRA AR MA RRA RA 5 6 5 4 5 2 5 1 4 9 4 7 4 3 3 3 300 re RARA AA AA RA 5 1 4 9 4 8 4 6 45 43 3 9 3 0 350 ex Henne Renee Kerne AMARE KAREKARE 46 4 4 4 3 4 1 4 0 3 6 28 400 seen nee Keen KAREKARE 43 4 1 4 0 3 9 3 7 3 4 2 6 450 9999 Henn KERKERAK ERROR RAMA RRA 3 9 3 8 3 6 3 5 3 2 2 5 500 5th cheek kd Ced 3 7 3 6 3 5 3 3 3 0 2 3 750 dokekdekdekek ekekdekdekek kkkkkkkk O dekdekdekdek kkkkkkkk dekdekdekdek kkkkkkkk kkkkkkkk kkkkkkkk AAA kkk 27 2 5 1 9 1000 KERN dekekdekdekek kkkkkkkk dekdekdekdek kkkkkkkk dekdekdekdek U KA ARA 24 1 7 1500 dokekdekdekek kkkkkkkk kkkkkkkk dekdekdekdek O dekdekdekdek kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkkkkkkk kkk kkk kk NOTE FOR CORRECT USAGE OF THESE TABLES PLEASE REFER TO MICRODATA DOCUMENTATION 3 The numerator of this ratio estimate is 237 261 The figure clos
20. This chapter presents a brief summary of the processing steps involved in producing these files 7 1 Data Capture As the data was collected using computer assisted telephone interviewing there was no need for a separate data capture system since the information was entered in the Regional Offices systems directly by the interviewers during the interview 7 2 Editing The first stage of survey processing was to merge the monthly files into a single file Any out of range values on the data file were replaced 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 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 Examples of derived variables include the average number of cigarettes smoked daily and the number of years the respond
21. ally exists 9 2 Sample Weighting Guidelines for Tabulation The sample design used for the Canadian Tobacco Use Monitoring Survey CTUMS was not self weighting When producing simple estimates including the production of ordinary statistical tables users must apply the proper sampling weight 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 Special Surveys Division 27 28 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 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 CTUMS data can be tabulated and analysed 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 CTUMS 9 3 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 people who currently smoke cigarettes or the proportion of daily smokers that have attempted to quit smoking are examples of such estimates An est
22. amely 2 5 4 So the approximate coefficient of variation of the estimate is 2 5 The finding that there were 5 414 335 to be rounded according to the rounding guidelines in Section 9 1 current smokers in the reference period is publishable with no qualifications Example 2 Estimates of Proportions or Percentages of Persons Possessing a Characteristic Suppose that the user estimates that 2 865 929 12 436 728 23 0 of men currently smoke in Canada in the reference period How does the user determine the coefficient of variation of this estimate 1 Refer to the Person coefficient of variation table for CANADA see above The CANADA level table should be used because it is the smallest table that contains the domain of the estimate all men in Canada 2 Because the estimate is a percentage which is based on a subset of the total population i e men it is necessary to use both the percentage 23 0 and the numerator portion of the percentage 2 865 929 in determining the coefficient of variation 3 The numerator 2 865 929 does not appear in the left hand column the Numerator of Percentage column so it is necessary to use the figure closest to it namely 3 000 000 Similarly the percentage estimate does not appear as any of the column headings so it is necessary to use the percentage closest to it 25 0 4 The figure at the intersection of the row and column used namely 3 1 is the coefficient of variation to be
23. ance a method exists which can make the variances calculated by the standard packages Special Surveys Division 29 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 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 2 calculate the AVERAGE weight for these 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 o
24. atios In this case Rules 3 and 4 are combined The CVs for the two ratios are first determined using Rule 4 and then the CV of their difference is found using Rule 3 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical Estimates The following examples based on the 2002 Annual data are included to assist users in applying the foregoing rules Please note that the data for these examples are different than the results obtained from the current survey and are only to be used as a guide Example 1 Estimates of Numbers of Persons Possessing a Characteristic Aggregates Suppose that a user estimates that during the reference period 5 414 335 persons were current smokers DVSST1 1 in Canada How does the user determine the coefficient of variation of this estimate 1 Refer to the Person coefficient of variation table for CANADA All Ages Canadian Tobacco Use Monitoring Survey 2002 February to December Person File Approximate Sampling Variability Tables for Canada All Ages NUM ERATOR OF ESTIMATED PERCENT AGE PERCENT AGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 197 2 196 3 195 3 192 3 187 1 181 9 176 4 170 8 165 0 159 0 152 8 139 5 108 0 139 4 138 8 138 1 135 9 132 3 128 6 124 8 120 8 116 7 112 5 108 0 98 6 76 4 113 8 113 3 112 7 111 0 108 0 105 0 101 9 98 6 95 3 91
25. ble below shows the conservative value of the design effects as well as sample sizes and population counts by province which were used to produce the Approximate Sampling Variability Tables for the Canadian Tobacco Use Monitoring Survey CTUMS Household file Household File Design Effect Sample Size Population bem mes sewn Special Surveys Division 35 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide The table below shows the conservative value of the design effects as well as sample sizes and population counts by province and age group which were used to produce the Approximate Sampling Variability Tables for the CTUMS Person file Person File Province Age Group Design Effect Sample Size Population Newfoundland and Labrador All 1 61 1 075 440 860 15 19 1 35 271 35 712 20 24 1 40 220 35 592 25 1 23 584 369 556 Prince Edward Island All 1 66 1 124 115 162 15 19 1 54 317 10 492 20 24 1 48 202 9 678 25 1 22 605 94 992 Nova Scotia All 1 87 1 261 779 289 15 19 1 40 332 64 099 20 24 1 34 296 62 797 25 1 30 633 652 393 New Brunswick All 1 84 1 100 622 665 15 19 1 34 274 49 162 20 24 1 40 257 49 896 25 1 33 569 523 607 Quebec All 1 80 1 172 6 207 636 15 19 1 51 293 454 687 20 24 1 32 281 503 875 25 1 31 598 5 249 074 Ontario All 1 77 1 130 10 059 894
26. cember 2004 22 8 2 Person Response Rates July to December 2004 23 8 3 SUIVey siio 25 8 4 Total Non resp nse rn ae E Ebo deoa sedie 25 8 5 Partial Non response 25 8 6 edhe Me erat ots aaaea Dra ste 25 8 7 Measurement of Sampling nennen 25 Guidelines for Tabulation Analysis and Release seen 27 9 1 Rounding Guidelines ssssssssssssesess esent nennen snnt tene 27 9 2 Sample Weighting Guidelines for Tabulation sseeeenes 27 9 3 Definitions of Types of Estimates Categorical and Quantitative 28 9 3 1 Categorical Estimates ssssssssssssssssesee esee nnne nennen nns 28 9 3 2 Quantitative Estimates uusnsssnsennsnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnnen 28 9 3 3 Tabulation of Categorical Estimates ssssssssee eene 29 9 8 4 Tabulation of Quantitative 29 9 4 Guidelines for Statistical Analysis sees 29 9 5 Coefficient of Variation Release Guidelines sss 30 9 6 Relea
27. continual and reliable data on tobacco use and related issues Since 1999 two CTUMS files have been released every year a file with data collected from February to June and a file with the July to December data Additionally there is also a yearly summary The present file covers the period from July to December 2004 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 3 0 Objectives The primary objective of the survey is to provide a continuous supply of smoking prevalence data against which changes in prevalence can be monitored This objective differs from that of the National Population Health Survey NPHS which collects smoking data from a longitudinal sample to measure which individuals are changing their smoking behaviour the possible factors which contribute to change and the possible risk factors related to starting smoking and smoking duration Because the NPHS collects data every two years and releases the data about a year after completing the collection cycle it does not meet Health Canada s need for continuous coverage in time rapid delivery of data or sufficient detail of the most at risk populations namely 15 to 24 year olds The Canadian Tobacco Use Monitoring Survey allows Health Canada to look at smoking prevalence by province sex age group for age groups 15 to 19 20 to 24 25 to 34 35 to 44 and 45 and over on a semi annual and annual basis Data will continue to be c
28. d correct outliers and to control who gets asked specific questions This meant that the data was already quite clean at the end of the collection process Interviewers were trained on the survey content and the CATI application In addition to classroom training the interviewers completed a series of mock interviews to become familiar with the survey and its concepts and definitions Every attempt is made to ensure that the same set of interviewers is used each month This minimizes training and yields better and more consistent data quality The cases were distributed to two of the Statistics Canada regional offices The workload and interviewing staff within each office was managed by a project manager The automated scheduler used by the CATI system ensured that cases were assigned randomly to interviewers and that cases were called at different times of the day and different days of the week to maximize the probability of contact There were a maximum of 20 call attempts per case identified as a residential phone number once the maximum was reached the case was reviewed by a senior interviewer who determined if additional calls would be made Special Surveys Division 17 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 7 0 Data Processing The main output of the Canadian Tobacco Use Monitoring Survey are two clean microdata files one for the household level information and one for the person level information
29. d proportions or percentages are relatively more reliable than the corresponding estimates of the numerator of the proportion or percentage when the proportion or percentage is based upon a sub group of the population For example the proportion of former smokers that quit for current health problems is more reliable than the estimated number of former smokers that quit for current health problems Note that in the tables the coefficients of variation decline in value when reading from left to right When the proportion or percentage is based upon the total population of the geographic area covered by the table the CV of the proportion or percentage is the same as the CV of the numerator of the proportion or percentage In this case Rule 1 can be used When the proportion or percentage is based upon a subset of the total population e g those in a particular sex or age group reference should be made to the proportion or percentage across the top of the table and to the numerator of the proportion or percentage down the left side of the table The intersection of the appropriate row and column gives the coefficient of variation Special Surveys Division 37 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Rule 3 Estimates of Differences Between Aggregates or Percentages The standard error of a difference between two estimates is approximately equal to the square root of the sum of squares of each standard error c
30. e 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 M 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 3 Unacceptable Estimates have a sample size of less than 30 or very high coefficients of variation in excess of 33 3 Statistics 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 U or some similar identifier and the following warning should accompany the estimates Please be warned that these estimates flagged with the letter U do not meet Statistics Canada s quality standards Conclusions based on these data will be unreliable and most likely invalid Special Surveys Division 31 32 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 9 6 Release Cut off s for the Canadian Tobacco Use Monitoring Survey Household File The minimum size of the estimates are specified in the table below by province for households Estimates smaller than the minimum size given in the Unacceptable column must be flagged in the appropriate manner Table of Release Cut offs House
31. ected person sub weight All in scope individuals were assigned weights The weight is inflated by the number of people within the selected age group and the inverse of the sub sampling factor wW W Number of individuals in selected age group d Sub sampling factor The sub sampling factor was 1 for age groups 15 to 19 and 20 to 24 The sub sampling factor was pre assigned for the 25 and over age group and varied from 23 296 to 33 496 depending on the province 11 Adjust for non responding individuals The Person file includes records of individual respondents who completed the questions on smoking habits and gave a date of birth corresponding to the age given in the roster There were 1 413 non respondents Thus 11 456 in scope individual weights were used and adjusted within province age groups derived from the roster 15 to 19 20 to 24 25 to 44 45 to 64 65 and over and sex M cmd for personrespondents W for person non respondents JO NW for person respondents Special Surveys Division 49 50 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 12 Adjust to external totals An adjustment was made to the person weights in order to make population estimates consistent with external population counts for persons 15 years and older This is known as post stratification The following external control totals were used 1 Monthly population totals for each province stratum and
32. elephone ownership 8 7 Measurement of Sampling Error Since it is an unavoidable fact that estimates from a sample survey are subject to sampling error sound statistical 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 Special Surveys Division 25 26 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 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 Annual 2002 survey results one estimates that 21 4 of Canadians are currently cigarette smokers and this estimate is found to have standard error of 0 0039 Then the coefficient of variation of the estimate is calculated as a X 100 1 8 0 214 There is more information on the calculation of
33. ent smoked The urban or rural character of the community where the respondent lives DVURBAN has been derived from the postal code The occupational category DVSOC10 is based on responses to questions LF_Q30 and LF_Q40 which were coded according to the 1991 Standard Occupational Classification SOC The 10 occupational categories correspond to the first digit of the classification 7 4 Weighting The principle behind estimation in a probability sample 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 people in Canada who smoke daily is to be estimated it is done by selecting the records referring to those individuals in the sample with that characteristic 55 Q10 1 and summing the weights entered on those records A separate weight for households and persons is calculated every six months Details of the method used to calculate these weights are presented in Chapter 11 0 Special Surveys Division 19 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 7 5 Suppression of Confidential Information It sh
34. est to it is 250 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row namely 5 6 4 The denominator of this ratio estimate is 220 511 The figure closest to it is 200 000 The coefficient of variation for this estimate is found by referring to the first non asterisk entry on that row namely 6 4 5 So the approximate coefficient of variation of the ratio estimate is given by Rule 4 which is 2 2 RT a a where a and are the coefficients of variation of X and X respectively That is a 4 0 056 0 064 0 003136 0 004096 0 085 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 6 The obtained ratio of women currently smoking in the age group 15 to 19 versus men currently smoking in the age group 15 to 19 is 237 261 220 511 which is 1 08 to be rounded according to the rounding guidelines in Section 9 1 The coefficient of variation of this estimate is 8 5 which makes the estimate releasable with no qualifications 10 2 How to Use the Coefficient of Variation Tables to Obtain Confidence Limits Although coefficients of variation are widely used a more intuitively meaningful measure of sampling error is the confidence interval of an estimate A confidence interval constitutes a statement on the level of confidence that the true value for the population lies within a specified ran
35. f Variation Release Guidelines Before releasing and or publishing any estimate from the Canadian Tobacco Use Monitoring Survey 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 fully 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 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Quality Level Guidelines Quality Level of Estimate 1 Acceptable Estimates have a sample siz
36. g between population parameters using sample estimates The sample estimates can be numbers averages percentages ratios etc Tests may be performed at various levels of significance where a level of significance is the probability of concluding that the characteristics are different when in fact they are identical Let x and X be sample estimates for two characteristics of interest Let the standard error on the difference X X be ET If L 3 is between 2 and 2 then no conclusion about the difference between the characteristics is justified at the 5 level of significance If however this ratio is smaller than 2 or larger than 2 the observed difference is significant at the 0 05 level That is to say that the difference between the estimates is significant 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test Let us suppose that the user wishes to test at 5 level of significance the hypothesis that there is no difference between the proportion of men who currently smoke and the proportion of women who currently smoke From Example 3 Section 10 1 1 the standard error of the difference between these two estimates was found to be 0 009 Hence Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide yl Rr W280 0199 2 0031 4 o 0 009 0 009 d Since t 3 44 is greater than 2 it must be concluded that there is a significant
37. ge of values For example a 95 confidence interval can be described as follows If sampling of the population is repeated indefinitely each sample leading to a new confidence interval for an estimate then in 95 of the samples the interval will cover the true population value Using the standard error of an estimate confidence intervals for estimates may be obtained under the assumption that under repeated sampling of the population the various estimates obtained for a population characteristic are normally distributed about the true population value Under this assumption the chances are about 68 out of 100 that the difference between a sample estimate and the true population value would be less than one standard error about 95 out of 100 that the difference would be less than two standard errors and about 99 out of 100 that the differences would be less than three standard errors These different degrees of confidence are referred to as the confidence levels Confidence intervals for an estimate X are generally expressed as two numbers one below the estimate and one above the estimate as k X k where kis determined depending upon the level of confidence desired and the sampling error of the estimate Confidence intervals for an estimate can be calculated directly from the Approximate Sampling Variability Tables by first determining from the appropriate table the coefficient of variation of the estimate X and then using the
38. group would be over represented with respect to the survey objectives Thus to save on the costs of additional interviews some of the selected people in the 25 and over age group were screened out and did not receive the tobacco use interview Two people were selected if more than one of the age groups 15 to 19 20 to 24 and 25 and over were represented in the household When two people in the same household were selected they were always from different age groups This ensured that there was no negative impact on the precision of the estimates by age group due to correlation within households There was a small impact on the precision for the total estimates for all ages but the sample size was sufficiently large so the impacts were minimal The detailed logic for the selection of individuals was as follows 1 If everyone in the household is 15 to 19 then one person is selected at random 2 If everyone in the household is 20 to 24 then one person is selected at random 3 If everyone in the household is 25 and over then one person is selected at random however this selected person is retained for only a proportion of the cases 4 If some household members are 15 to 19 and the rest are 20 to 24 then two people are selected at random one from each age group 5 If some household members are 15 to 19 and the rest are 25 and over then two people are selected at random one from each age group however the person selected from the 25 and over
39. hold File Province Acceptable CV Marginal CV Unacceptable CV 0 0 to 16 5 16 6 to 33 3 gt 33 3 Newfoundland and Labrador Prince Edward Island Nova Scotia New Brunswick Quebec Ontario 29 000 amp over 10500 to lt 43 000 under 10500 Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 9 7 Release Cut off s for the Canadian Tobacco Use Monitoring Survey Person File The minimum size of the estimates are specified in the table below by province and age group Estimates smaller than the minimum size given in the Unacceptable column must be flagged in the appropriate manner Table of Release Cut offs Person File Acceptable CV Marginal CV Unacceptable CV Group 0 0 to 16 5 16 6 to 33 3 gt 33 3 Newfoundland and Labrador 6 000 to 23 000 1 500 to 5 500 2 000 to lt 6 500 7 000 to lt 26 500 Prince Edward Island 1 500 to 6 000 500 to 1 500 500 to 2 000 15 000 to lt 6 500 Nova Scotia 40 000 amp over 10 500 to 40 000 under 10 500 15 19 8 500 amp over 2 500 to 8 500 under 2 500 2 500 to lt 9000 12 000 lt 46 000 New Brunswick 9 500_to lt 36 000 2 000_to lt 7 500 2 500_to lt 8 500 11 000_to lt 41 500 Quebec 20 000 to lt 72 500 20 500 to lt 74000 Ontario Manitoba 12 500_to lt 49 000 3 500 to lt 13 000 4 000 to lt 14 000 15 000 to 57 000 Saskatchewan 9 000 to lt 36 000 3 000 to lt 11 000 3 500 to
40. ile Additionally when the sum of household members derived from the information about their age ranges exceeded five the maximum value of the household size variable HHSIZE the age range variables 15 to 24 25 to 44 and 45 were modified On those records all the age ranges present in the household were maintained but some of them had the value two or more replaced with one There were 184 such modifications on the Household file and 170 on the Person file Person File Only Geographic Identifiers Starting with Cycle 1 of 2002 the master data file contains the first three digits of the respondent s postal code Since Cycle 2 2003 the master and the public use microdata files contain an urban rural variable DVURBAN This 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 areas have minimum population concentrations of 1 000 people anda 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 Marital Status The detailed marital status variable six categories is available on the master file only while on the public use microdata file this variable has been grouped into three categories Level of Education The detailed level of education variable has been replaced with a version of the variable where
41. imate of the number of persons possessing a certain characteristic may also be referred to as an estimate of an aggregate Examples of Categorical Questions Q Inthe past 30 days did you smoke any cigarettes Yes No R Q What was your main reason to quit smoking R Health Pregnancy or a baby in the household Less stress in life Cost of cigarettes Smoking is less socially acceptable 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 Y where X isan estimate of surveyed population quantity total and Y is an estimate of the number of persons in the surveyed population contributing to that total quantity An example of a quantitative estimate is the average number of cigarettes smoked on Saturday per person The numerator X J is an estimate of the total number of cigarettes smoked on Saturday and its denominator is the number of persons who reported smoking on Saturday Examples of Quantitative Questions Q Some people smoke more or less depending on the day of the week So thinking back over the past 7 days starting with yesterday how many cigarettes did you smoke Saturday _ _ cigarettes R Q At what age did you smoke your first cigarette _ _ years old S
42. is less than 30 the weighted estimate should be considered unacceptable and should be flagged in the appropriate manner regardless of the value of the coefficient of variation for this estimate This is because the formulas used for estimating the variance do not hold true for small sample sizes 10 1 How to Use the Coefficient of Variation Tables for Categorical Estimates The following rules should enable the user to determine the approximate coefficients of variation from the Approximate Sampling Variability Tables for estimates of the number proportion or percentage of the surveyed population possessing a certain characteristic and for ratios and differences between such estimates Rule 1 Estimates of Numbers of Persons Possessing a Characteristic Aggregates The coefficient of variation depends only on the size of the estimate itself On the Approximate Sampling Variability Table for the appropriate geographic area locate the estimated number in the left most column of the table headed Numerator of Percentage and follow the asterisks if any across to the first figure encountered This figure is the approximate coefficient of variation Rule 2 Estimates of Proportions or Percentages of Persons Possessing a Characteristic The coefficient of variation of an estimated proportion or percentage depends on both the size of the proportion or percentage and the size of the total upon which the proportion or percentage is based Estimate
43. ithout telephones 5 2 Stratification In order to ensure that people from all parts of Canada were represented in the sample each of the 10 provinces were divided into strata or geographic areas Generally within each province a census metropolitan area CMA stratum and a non CMA stratum was defined In Prince Edward Island there was only one stratum for the province In Ontario there was a third stratum for Toronto and in Quebec there was a third stratum for Montreal CMAs are areas defined by the census and correspond roughly to the cities with populations of 100 000 or more 5 3 Sample Design and Allocation The sample design is a special two phase stratified random sample of telephone numbers The two phase design is used in order to increase the representation in the sample of individuals belonging to the 15 to 19 and 20 to 24 age groups In the first phase households are selected using RDD In the second phase one or two individuals or none are selected based upon household composition Because the main purpose of the survey is to produce reliable estimates in all 10 provinces an equal number of respondents in each province is targeted The target is to get responses from 5 000 individuals aged 15 to 24 and 5 000 individuals aged 25 and over across Canada or 500 individuals in each age group per province The initial sample size of telephone numbers depended upon the expected response rate and the expected RDD hit rate proportio
44. m of 4 that serviced the household The adjustment was done within province stratum month W W T of in scope telephone lines in the household 6 Adjust for non responding households Household respondents responded to the questions on their smoking habits If these questions were not sufficiently answered perhaps refused or only partially answered then the household was considered a non respondent There were 472 non respondents Thus 25 855 in scope household weights were used and adjusted within province stratum month NW for household respondents yz W for household non W for household respondents 11 2 Weighting Procedures for the Household File 7 Adjust to known external household stratum totals An adjustment was made to the household weights on records within each province stratum and month in order to make household estimates consistent with known external household counts The adjustment factor for province stratum month P S M was defined as Known external household count in P S M Ws W5 Ss w for responding households in the sample in P S M The household weights W obtained after this step were considered final and appear on the household microdata file Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 11 3 Weighting Procedures for the Person File 7 Remove households with no selected
45. n of sampled telephone numbers which are screened in as households To achieve the required sample sizes two adjustments to the standard RDD methodology were introduced First the probabilities of selection within the household were unequal and second households with only persons aged 25 and over present were sub sampled It is estimated that a total of almost 130 000 telephone numbers per year will be needed to get the 20 000 respondents per year This assumed a 75 response rate and about 20 of households having individuals aged 15 to 24 the hit rate varies substantially by province with an expected overall average of about 4096 Special Surveys Division 13 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 5 4 Sample Selection The sample for the Canadian Tobacco Use Monitoring Survey was generated using a refinement of RDD sampling called the Elimination of Non Working Banks ENWB Within each province stratum combination a list of working banks area code next five digits was compiled from telephone company administrative files A working bank for the purposes of social surveys is defined as a bank which contains at least one working residential telephone number Thus all banks with only unassigned non working or business telephone numbers are excluded from the survey frame Next a systematic sample of banks with replacement was selected within each stratum For each selected bank a two digit number 00
46. no schooling and some elementary categories have been grouped Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 8 0 Data Quality For the Canadian Tobacco Use Monitoring Survey CTUMS the response rates computed include the following Household File and Person File Telephone Resolved Rate is the proportion of sampled telephone numbers that were confirmed as residential or out of scope e g business or non working numbers thus were considered resolved residential or out of scope numbers sampled telephone numbers Hit Rate is the proportion of resolved telephone numbers that were confirmed as residential or had valid household data residential numbers or valid household data resolved telephone numbers Roster Completion Rate is the proportion of households with a complete roster containing ages for each household member this is a necessary condition for considering a household and a person record a response households with complete roster total households i e numbers resolved as residential Household Response Rate is the proportion of households with a complete roster ages provided for everyone in the roster and with valid household data households with complete roster and valid household data total households i e numbers resolved as residential Person File Only Person Response Rate is the proportion of records of selected persons with co
47. observation of interviewers to detect problems of questionnaire design or misunderstanding of instructions and testing of the CATI application to ensure that range checks edits and question flow were all programmed correctly 8 4 Total Non response Total non response can be a major source of non sampling error in many surveys depending on the degree to which respondents and non respondents differ with respect to the characteristics of interest Total non response occurred because the interviewer was either unable to contact the respondent or the respondent refused to participate in the survey Total non response was handled by adjusting the weight of households or individuals who responded to the survey to compensate for those who did not respond 8 5 Partial Non response In most cases partial 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 Partial non response is indicated by codes on the microdata file i e refused don t know 8 6 Coverage As mentioned in Section 5 1 Population Coverage less than 3 of households in Canada do not have telephones Individuals living in non telephone households may have unique characteristics which will not be reflected in the survey estimates Users should be cautious when analyzing subgroups of the population which have characteristics that may be correlated with non t
48. ollected on an on going basis depending on availability of funds Special Surveys Division 9 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 4 0 Concepts and Definitions Since the Canadian Tobacco Use Monitoring Survey is conducted over the telephone easy to understand terminology is used throughout the questionnaire to avoid long explanations Some standard concepts and definitions should be used in the analysis and interpretation of this data The survey questions were designed with these definitions in mind Current Smoking Status 1 Daily smoker A person who currently smokes cigarettes every day 2 Non daily smoker A person who currently smokes cigarettes but not every day 3 Non smoker A person who currently does not smoke cigarettes 4 Current smoker A person who currently smokes cigarettes daily or occasionally Smoking History _ Former smoker A person who has smoked at least 100 cigarettes in his life but currently does not smoke 2 Experimental smoker person who has smoked at least one cigarette but less than 100 cigarettes and currently does not smoke cigarettes 3 Lifetime abstainer A person who has never smoked cigarettes at all 4 Ever smoker A person who is a current smoker or a former smoker 5 Never smoker A person who was an experimental smoker or who is a lifetime abstainer Smoking Prevalence Proportion of population which smokes cigarettes at the current time
49. on response adjustment for telephone non response had been applied Note that if household or person data existed then the telephone number was assumed to be a household There were 40 303 out of scope telephone numbers and 30 425 telephone numbers belonging to a household Special Surveys Division 47 48 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 4 Adjust for non response of number of telephone lines in the household The number of telephone lines in the household was calculated If the number of different telephone lines within the household could not be calculated but household or person data existed then it was imputed as one in order to retain good data After imputation there were 4 098 telephone numbers that were still missing the number of lines Thus there were 26 327 households with the number of lines calculated or imputed The adjustment was done within province stratum month W W Sw for households with number of lines for households mis sin g number of 3 2 y W for households with number of lines 5 Calculate household weight with multiple telephone lines adjustment Weights for households with more than one telephone line with different telephone numbers were adjusted downwards to account for the fact that such households have a higher probability of being selected The weight for each household was divided by the number of distinct residential telephone lines up to a maximu
50. onsidered separately That is the standard error of a difference X g is o y Ria where X is estimate 1 X is estimate 2 and and are the coefficients of variation of X and X respectively The coefficient of variation of d is given by d This formula is accurate for the difference between separate and uncorrelated characteristics but is only approximate otherwise Rule 4 Estimates of Ratios In the case where the numerator is a subset of the denominator the ratio should be converted to a percentage and Rule 2 applied This would apply for example to the case where the denominator is the number of smokers and the numerator is the number of daily smokers In the case where the numerator is not a subset of the denominator as for example the ratio of the number of daily smokers as compared to the number of non smokers the standard error of the ratio of the estimates is approximately equal to the square root of the sum of squares of each coefficient of variation considered separately multiplied by R That is the standard error of a ratio R X 1X is D 2 2 O Ry a 9 where and are the coefficients of variation of X and X respectively The coefficient of variation of R is given by om The formula will tend to overstate the error if x and X are positively correlated and understate the error if X and X are negatively correlated Rule 5 Estimates of Differences of R
51. or the Household and Person Files 1 Calculate telephone weight Each telephone number in the sample was assigned a basic weight W equal to the inverse of its probability of selection W number of possible sampled telephone numbers in province stratum ent Number of sampled telephone numbers in province stratum month There were 75 739 telephone numbers in the sample with assigned weights 2 Adjust for non resolved telephone numbers There were 5 011 telephone numbers that were not resolved leaving 70 728 resolved telephone numbers The unresolved telephone numbers were not determined to belong to a household business or out of scope Each telephone number had a flag indicating whether it was expected to be a residential business or unknown type of telephone number and a flag indicating whether or not it was screened out before collection as a non working or business number The adjustment for the unresolved telephone numbers was done within province stratum month the expected line type and whether or not the number was sent to the field For each province stratum month expected line type sent qe gt W for resolved telephone numbers SW forunresolved telephone numbers a SW for resolved telephone numbers 3 Remove out of scope telephone numbers Telephone numbers corresponding to businesses out of service numbers or out of scope numbers such as cottage telephone numbers were dropped after the n
52. ould be noted that the Public Use Microdata 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 the suppression of file 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 Household File and Person File Geographic Identifiers The survey s master data files include explicit geographic identifiers for province and stratum census metropolitan area CMA non CMA Toronto or Montreal The survey s public use microdata files only contain an identifier for province Household Age Composition Household age composition is available as the number of household members capped at two in the following age ranges 0 to 14 15 to 24 25 to 44 and 45 and over Other Modifications to the Household File and Person File A small number of records on the household file below 10 had a demographic variable recoded to avoid potential identification of respondents resulting from an unusual combination of characteristics Similar recoding also took place on the person f
53. pecial Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 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 a summing the final weights of records having the characteristic of interest for the numerator X J b summing the final weights of records having the characteristic of interest for the denominator Y J then c divide estimate a by estimate b x 17 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 cigarettes smoked on Saturday multiply the value reported in question WP_Q10F number of cigarettes smoked on Saturday by the final weight for the record then sum this value over all records with WP_Q10F lt 96 all respondents who reported a value in this field To obtain a weighted average of the form XIY the numerator x is calculated as for a quantitative estimate and the denominator f is calculated as for a categorical estimate For example to estimate the average number of cigare
54. persons There were 14 631 households where no one was selected to continue with the tobacco use survey or a selected person was not retained because of sub selection of individuals These households were dropped because they had no person level data About 70 of selected respondents aged 25 and over were screened out There were 11 224 households with selected persons There were 9 579 households with one person selected and 1 645 with two people selected 8 Calculate group weight All of the in scope responding households with completed rosters i e no missing ages were assigned group weights From the roster three flags were assigned to indicate the presence of a person in the following age groups 15 to 19 20 to 24 and 25 and over If one or two age group categories were represented then an individual was selected from each age group present i e the probability of selection of the age group was 1 Thus the weight was not inflated However if three age groups were represented then two people were selected so the probability of selecting the age group is 2 out of the 3 groups Thus the weight is inflated by its inverse If 1 or 2 age groups were represented then W W If all 3 age groups were represented then W W 3 2 9 Assign household weights to selected persons The 9 579 2 1 645 12 869 selected persons are associated with in scope responding households and keep the corresponding weight W 10 Calculate sel
55. rom replicate to replicate Users wishing to derive coefficients of variation for quantitative estimates may contact Statistics Canada for advice on the allocation of records to appropriate replicates and the formulae to be used in these calculations 10 5 Coefficient of Variation Tables Household File Refer to CTUMS2004 C2 HH OVTabsE pdf for the coefficient of variation tables for the Household file for Cycle 2 of 2004 10 6 Coefficient of Variation Tables Person File Refer to CTUMS2004 C2 PR OCVTabsE pdf for the coefficient of variation tables for the Person file for Cycle 2 of 2004 Special Surveys Division 45 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide 11 0 Weighting For the microdata file statistical weights were placed on each record to represent the number of sampled households or persons that the record represents One weight was calculated for each household and a separate weight was calculated and provided on a different file for each person The weighting for the Canadian Tobacco Use Monitoring Survey consisted of several steps calculation of a basic weight adjustments for non response an adjustment for selecting one or two persons in the household dropping out of scope records and finally an adjustment to make the populations estimates consistent with known province age sex totals from the Census projected population counts for persons 15 years and over 11 1 Weighting Procedures f
56. rresponding complete roster and valid household data whose records had valid person data persons with complete roster with valid household data and valid person data all selected persons with complete household roster and valid household data Overall Response Rate for the survey fully reflects the response rate at the person level by combining response rates at the household and the person level Household Response Rate x Person Response Rate Special Surveys Division 21 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Telephone Resolved Rate and Hit Rate by Province Number of Telephone Numbers Generated Total Telephone Households Roster Hit Resolved Resolved Number of with Valid Completion Rate Numbers Rate Households Roster Data Rate Labrador rince Edward Island 7 457 6 823 2 748 2 435 Nova Scotia 8 001 7 433 3 193 2 878 New Brunswick Quebec Ontario askatchewan 8 1 Household Response Rates July to December 2004 A household respondent must complete the roster with no age refusals and valid household data must exist There were 4 570 15 0 households that were non responding 2 515 of these households 8 3 of total households refused participation Household Response Rate by Province Total Number of Number et Household Responding Households Households Response Rate Newfoundland and Labrador Prince Edward Island Nova Scotia
57. se Cut off s for the Canadian Tobacco Use Monitoring Survey Household File 32 9 7 Release Cut off s for the Canadian Tobacco Use Monitoring Survey Person File 33 10 0 12 0 13 0 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Approximate Sampling Variability 35 10 1 Howto Use the Coefficient of Variation Tables for Categorical Estimates 37 10 1 1 Examples of Using the Coefficient of Variation Tables for Categorical zi nud T TET E 39 10 2 Howto Use the Coefficient of Variation Tables to Obtain Confidence Limits 43 10 2 1 Example of Using the Coefficient of Variation Tables to Obtain Confidence O 44 10 3 How to Use the Coefficient of Variation Tables to Do a 44 10 3 1 Example of Using the Coefficient of Variation Tables to Do a T test 44 10 4 Coefficient of Variation for Quantitative Estimates 45 10 5 Coefficient of Variation Tables Household File seem 45 10 6 Coefficient of Variation Tables Person File 45 Weighlihig c A e eae etae eund c eet eund nans 47 11 1 Weighting Procedures for the Household and Person
58. tics Canada recommends this estimate not be released However should the user choose to do so the estimate should be flagged with the letter M or some similar identifier and be accompanied by a warning to caution subsequent users about the high levels of error associated with the estimate Example 4 Estimates of Ratios Suppose that the user estimates that 237 261 women currently smoke in the age group 15 to 19 while 220 511 men currently smoke in the age group 15 to 19 The user is interested in comparing the estimate of women versus that of men in the form of a ratio How does the user determine the coefficient of variation of this estimate 1 First of all this estimate is a ratio estimate where the numerator of the estimate X is the number of women currently smoking in the age group 15 to 19 The denominator of the estimate X is the number of men currently smoking in the age group 15 to 19 2 Refer to the Person coefficient of variation table for CANADA 15 19 Special Surveys Division 41 Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide Canadian Tobacco Use Monitoring Survey 2002 February to December Person File Approximate Sampling Variability Tables for Canada 15 19 NUM ERATOR OF ESTIMATED PERCENTAGE PERCENTAGE 000 0 1 1 0 2 0 5 0 10 0 15 0 20 0 25 0 30 0 35 0 40 0 50 0 70 0 90 0 95 8 95 3 94 9 93 4 90 9 88 3 85 7 83 0 80 2 77 3 74 2 67 8 52 5 30 3 67 7 67 4 67 1 66 0
59. to 99 was generated at random This random number was added to the bank to form a complete telephone number This method allowed listed and unlisted residential numbers as well as business and non working numbers i e not currently or never in service to have a chance of being in the sample A screening activity aimed at removing not in service and known business numbers was performed prior to sending the sample to the computer assisted telephone interviewing CATI unit Each telephone number in the CATI sample was dialled to determine whether or not it reached a household If the telephone number is found to reach a household the person answering the telephone was asked to provide information on the individual household members The ages of the household members were used to determine who in the household would be selected for the tobacco use interview Proxy interviews were not accepted To ensure that enough people were reached in the younger age groups the random selection was set up such that at least one person aged 15 to 19 or 20 to 24 would be selected within a household if they exist The reason for this is that about 7696 of all households in Canada are made up of only people over 25 years of age another 2096 consist of people over 25 living with people in either the 15 to 19 or 20 to 24 age group and only 4 of households contain no one aged over 25 If all ages were selected with equal probability and retained the 25 and over age
60. ttes smoked on Saturday a estimate the total number of cigarettes smoked on Saturday above as described b estimate the number of people 7 in this category by summing the final weights of all records with WP_Q10F lt 96 then c divide estimate a by estimate b x 9 4 Guidelines for Statistical Analysis The Canadian Tobacco Use Monitoring Survey 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 Approximate variances for simple estimates such as totals proportions and ratios for qualitative variables can be derived using the accompanying Approximate Sampling Variability Tables For other analysis techniques for example linear regression logistic regression and analysis of vari
61. used 5 So the approximate coefficient of variation of the estimate is 3 1 The finding that 23 0 of men currently smoke can be published with no qualifications Example 3 Estimates of Differences Between Aggregates or Percentages Suppose that a user estimates that 2 548 406 12 814 359 19 9 of women currently smoke in Canada while 2 865 929 12 436 728 23 0 of men currently smoke in Canada How does the user determine the coefficient of variation of the difference between these two estimates 1 Using the Person CANADA coefficient of variation table see above in the same manner as described in Example 2 gives the CV of the estimate for women as 3 2 and the CV of the estimate for men as 3 1 2 Using Rule 3 the standard error of a difference X X is A X a a Special Surveys Division Canadian Tobacco Use Monitoring Survey Cycle 2 2004 User Guide where X is estimate 1 men X is estimate 2 women and and are the coefficients of variation of X and x respectively That is the standard error of the difference d 0 230 0 199 0 031 is e llo 2300 031 F 0 199 0 032 0 00005 0 00004 0 009 3 The coefficient of variation of d is given by 0 009 0 031 0 290 4 So the approximate coefficient of variation of the difference between the estimates is 29 0 The difference between the estimates is considered marginal and Statis
62. yout with univariate counts for the Person file for Cycle 2 of 2004 Special Surveys Division 53

Microdata User Guide CANADIAN TOBACCO USE MONITORING

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