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All (98) (0 to 10 of 98 results)

  • Articles and reports: 75F0002M2004012
    Description:

    This study compares income estimates across several statistical programs at Statistics Canada. It examines how similar the estimates produced by different question sets are.

    Income data are collected by many household surveys. Some surveys have income as a major part of their content, and therefore collect income at a detailed level; others collect data from a much smaller set of income questions. No standard sets of income questions have been developed.

    Release date: 2004-12-23

  • Journals and periodicals: 92-395-X
    Description:

    This report describes sampling and weighting procedures used in the 2001 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

    Release date: 2004-12-15

  • Surveys and statistical programs – Documentation: 62F0026M2004003
    Geography: Province or territory
    Description:

    This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households.

    This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the statistics that can be created using expenditure data (e.g., budget share, market share and aggregates).

    Release date: 2004-12-13

  • Surveys and statistical programs – Documentation: 92-394-X
    Description:

    This report deals with coverage errors that occur when persons, households, dwellings or families are missed or enumerated in error by the census. After the 2001 Census was taken, a number of studies were carried out to estimate gross undercoverage, gross overcoverage and net undercoverage. This report presents the results of the Dwelling Classification Study, the Reverse Record Check Study, the Automated Match Study and the Collective Dwelling Study. The report first describes census universes, coverage error and census collection and processing procedures that may result in coverage error. Then it gives estimates of net undercoverage for a number of demographic characteristics. After, the technical report presents the methodology and results of each coverage study and the estimates of coverage error after describing how the results of the various studies are combined. A historical perspective completes the product.

    Release date: 2004-11-25

  • Surveys and statistical programs – Documentation: 13-604-M2004045
    Description:

    How "good" are the National Tourism Indicators (NTI)? How can their quality be measured? This study looks to answer these questions by analysing the revisions to the NTI estimates for the period 1997 through 2001.

    Release date: 2004-10-25

  • Table: 53-500-X
    Description:

    This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.

    Release date: 2004-10-21

  • Surveys and statistical programs – Documentation: 31-533-X
    Description:

    Starting with the August 2004 reference month, the Monthly Survey of Manufacturing (MSM) is using administrative data (Goods and Services Tax files) to derive shipments for a portion of the small establishments in the sample. This document is being published to complement the release of MSM data for that month.

    Release date: 2004-10-15

  • Articles and reports: 75F0002M2004010
    Description:

    This document offers a set of guidelines for analysing income distributions. It focuses on the basic intuition of the concepts and techniques instead of the equations and technical details.

    Release date: 2004-10-08

  • Articles and reports: 12-002-X20040027032
    Description:

    This article examines why many Statistics Canada surveys supply bootstrap weights with their microdata for the purpose of design-based variance estimation. Bootstrap weights are not supported by commercially available software such as SUDAAN and WesVar, but there are ways to use these applications to produce boostrap variance estimates.

    The paper concludes with a brief discussion of other design-based approaches to variance estimation as well as software, programs and procedures where these methods have been employed.

    Release date: 2004-10-05

  • Articles and reports: 12-002-X20040027034
    Description:

    The use of command files in Stat/Transfer can expedite the transfer of several data sets in an efficient replicable manner. This note outlines a simple step-by-step method for creating command files and provides sample code.

    Release date: 2004-10-05
Data (1)

Data (1) ((1 result))

  • Table: 53-500-X
    Description:

    This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.

    Release date: 2004-10-21
Analysis (74)

Analysis (74) (0 to 10 of 74 results)

  • Articles and reports: 75F0002M2004012
    Description:

    This study compares income estimates across several statistical programs at Statistics Canada. It examines how similar the estimates produced by different question sets are.

    Income data are collected by many household surveys. Some surveys have income as a major part of their content, and therefore collect income at a detailed level; others collect data from a much smaller set of income questions. No standard sets of income questions have been developed.

    Release date: 2004-12-23

  • Journals and periodicals: 92-395-X
    Description:

    This report describes sampling and weighting procedures used in the 2001 Census. It reviews the history of these procedures in Canadian censuses, provides operational and theoretical justifications for them, and presents the results of the evaluation studies of these procedures.

    Release date: 2004-12-15

  • Articles and reports: 75F0002M2004010
    Description:

    This document offers a set of guidelines for analysing income distributions. It focuses on the basic intuition of the concepts and techniques instead of the equations and technical details.

    Release date: 2004-10-08

  • Articles and reports: 12-002-X20040027032
    Description:

    This article examines why many Statistics Canada surveys supply bootstrap weights with their microdata for the purpose of design-based variance estimation. Bootstrap weights are not supported by commercially available software such as SUDAAN and WesVar, but there are ways to use these applications to produce boostrap variance estimates.

    The paper concludes with a brief discussion of other design-based approaches to variance estimation as well as software, programs and procedures where these methods have been employed.

    Release date: 2004-10-05

  • Articles and reports: 12-002-X20040027034
    Description:

    The use of command files in Stat/Transfer can expedite the transfer of several data sets in an efficient replicable manner. This note outlines a simple step-by-step method for creating command files and provides sample code.

    Release date: 2004-10-05

  • Articles and reports: 11-522-X20020016430
    Description:

    Linearization (or Taylor series) methods are widely used to estimate standard errors for the co-efficients of linear regression models fit to multi-stage samples. When the number of primary sampling units (PSUs) is large, linearization can produce accurate standard errors under quite general conditions. However, when the number of PSUs is small or a co-efficient depends primarily on data from a small number of PSUs, linearization estimators can have large negative bias.

    In this paper, we characterize features of the design matrix that produce large bias in linearization standard errors for linear regression co-efficients. We then propose a new method, bias reduced linearization (BRL), based on residuals adjusted to better approximate the covariance of the true errors. When the errors are independent and identically distributed (i.i.d.), the BRL estimator is unbiased for the variance. Furthermore, a simulation study shows that BRL can greatly reduce the bias, even if the errors are not i.i.d. We also propose using a Satterthwaite approximation to determine the degrees of freedom of the reference distribution for tests and confidence intervals about linear combinations of co-efficients based on the BRL estimator. We demonstrate that the jackknife estimator also tends to be biased in situations where linearization is biased. However, the jackknife's bias tends to be positive. Our bias-reduced linearization estimator can be viewed as a compromise between the traditional linearization and jackknife estimators.

    Release date: 2004-09-13

  • Articles and reports: 11-522-X20020016708
    Description:

    In this paper, we discuss the analysis of complex health survey data by using multivariate modelling techniques. Main interests are in various design-based and model-based methods that aim at accounting for the design complexities, including clustering, stratification and weighting. Methods covered include generalized linear modelling based on pseudo-likelihood and generalized estimating equations, linear mixed models estimated by restricted maximum likelihood, and hierarchical Bayes techniques using Markov Chain Monte Carlo (MCMC) methods. The methods will be compared empirically, using data from an extensive health interview and examination survey conducted in Finland in 2000 (Health 2000 Study).

    The data of the Health 2000 Study were collected using personal interviews, questionnaires and clinical examinations. A stratified two-stage cluster sampling design was used in the survey. The sampling design involved positive intra-cluster correlation for many study variables. For a closer investigation, we selected a small number of study variables from the health interview and health examination phases. In many cases, the different methods produced similar numerical results and supported similar statistical conclusions. Methods that failed to account for the design complexities sometimes led to conflicting conclusions. We also discuss the application of the methods in this paper by using standard statistical software products.

    Release date: 2004-09-13

  • Articles and reports: 11-522-X20020016712
    Description:

    In this paper, we consider the effect of the interval censoring of cessation time on intensity parameter estimation with regard to smoking cessation and pregnancy. The three waves of the National Population Health Survey allow the methodology of event history analysis to be applied to smoking initiation, cessation and relapse. One issue of interest is the relationship between smoking cessation and pregnancy. If a longitudinal respondent who is a smoker at the first cycle ceases smoking by the second cycle, we know the cessation time to within an interval of length at most a year, since the respondent is asked for the age at which she stopped smoking, and her date of birth is known. We also know whether she is pregnant at the time of the second cycle, and whether she has given birth since the time of the first cycle. For many such subjects, we know the date of conception to within a relatively small interval. If we knew the time of smoking cessation and pregnancy period exactly for each member who experienced one or other of these events between cycles, we could model their temporal relationship through their joint intensities.

    Release date: 2004-09-13

  • Articles and reports: 11-522-X20020016714
    Description:

    In this highly technical paper, we illustrate the application of the delete-a-group jack-knife variance estimator approach to a particular complex multi-wave longitudinal study, demonstrating its utility for linear regression and other analytic models. The delete-a-group jack-knife variance estimator is proving a very useful tool for measuring variances under complex sampling designs. This technique divides the first-phase sample into mutually exclusive and nearly equal variance groups, deletes one group at a time to create a set of replicates and makes analogous weighting adjustments in each replicate to those done for the sample as a whole. Variance estimation proceeds in the standard (unstratified) jack-knife fashion.

    Our application is to the Chicago Health and Aging Project (CHAP), a community-based longitudinal study examining risk factors for chronic health problems of older adults. A major aim of the study is the investigation of risk factors for incident Alzheimer's disease. The current design of CHAP has two components: (1) Every three years, all surviving members of the cohort are interviewed on a variety of health-related topics. These interviews include cognitive and physical function measures. (2) At each of these waves of data collection, a stratified Poisson sample is drawn from among the respondents to the full population interview for detailed clinical evaluation and neuropsychological testing. To investigate risk factors for incident disease, a 'disease-free' cohort is identified at the preceding time point and forms one major stratum in the sampling frame.

    We provide proofs of the theoretical applicability of the delete-a-group jack-knife for particular estimators under this Poisson design, paying needed attention to the distinction between finite-population and infinite-population (model) inference. In addition, we examine the issue of determining the 'right number' of variance groups.

    Release date: 2004-09-13

  • Articles and reports: 11-522-X20020016715
    Description:

    This paper will describe the multiple imputation of income in the National Health Interview Survey and discuss the methodological issues involved. In addition, the paper will present empirical summaries of the imputations as well as results of a Monte Carlo evaluation of inferences based on multiply imputed income items.

    Analysts of health data are often interested in studying relationships between income and health. The National Health Interview Survey, conducted by the National Center for Health Statistics of the U.S. Centers for Disease Control and Prevention, provides a rich source of data for studying such relationships. However, the nonresponse rates on two key income items, an individual's earned income and a family's total income, are over 20%. Moreover, these nonresponse rates appear to be increasing over time. A project is currently underway to multiply impute individual earnings and family income along with some other covariates for the National Health Interview Survey in 1997 and subsequent years.

    There are many challenges in developing appropriate multiple imputations for such large-scale surveys. First, there are many variables of different types, with different skip patterns and logical relationships. Second, it is not known what types of associations will be investigated by the analysts of multiply imputed data. Finally, some variables, such as family income, are collected at the family level and others, such as earned income, are collected at the individual level. To make the imputations for both the family- and individual-level variables conditional on as many predictors as possible, and to simplify modelling, we are using a modified version of the sequential regression imputation method described in Raghunathan et al. ( Survey Methodology, 2001).

    Besides issues related to the hierarchical nature of the imputations just described, there are other methodological issues of interest such as the use of transformations of the income variables, the imposition of restrictions on the values of variables, the general validity of sequential regression imputation and, even more generally, the validity of multiple-imputation inferences for surveys with complex sample designs.

    Release date: 2004-09-13
Reference (23)

Reference (23) (0 to 10 of 23 results)

  • Surveys and statistical programs – Documentation: 62F0026M2004003
    Geography: Province or territory
    Description:

    This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households.

    This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the statistics that can be created using expenditure data (e.g., budget share, market share and aggregates).

    Release date: 2004-12-13

  • Surveys and statistical programs – Documentation: 92-394-X
    Description:

    This report deals with coverage errors that occur when persons, households, dwellings or families are missed or enumerated in error by the census. After the 2001 Census was taken, a number of studies were carried out to estimate gross undercoverage, gross overcoverage and net undercoverage. This report presents the results of the Dwelling Classification Study, the Reverse Record Check Study, the Automated Match Study and the Collective Dwelling Study. The report first describes census universes, coverage error and census collection and processing procedures that may result in coverage error. Then it gives estimates of net undercoverage for a number of demographic characteristics. After, the technical report presents the methodology and results of each coverage study and the estimates of coverage error after describing how the results of the various studies are combined. A historical perspective completes the product.

    Release date: 2004-11-25

  • Surveys and statistical programs – Documentation: 13-604-M2004045
    Description:

    How "good" are the National Tourism Indicators (NTI)? How can their quality be measured? This study looks to answer these questions by analysing the revisions to the NTI estimates for the period 1997 through 2001.

    Release date: 2004-10-25

  • Surveys and statistical programs – Documentation: 31-533-X
    Description:

    Starting with the August 2004 reference month, the Monthly Survey of Manufacturing (MSM) is using administrative data (Goods and Services Tax files) to derive shipments for a portion of the small establishments in the sample. This document is being published to complement the release of MSM data for that month.

    Release date: 2004-10-15

  • Surveys and statistical programs – Documentation: 12-002-X20040027035
    Description:

    As part of the processing of the National Longitudinal Survey of Children and Youth (NLSCY) cycle 4 data, historical revisions have been made to the data of the first 3 cycles, either to correct errors or to update the data. During processing, particular attention was given to the PERSRUK (Person Identifier) and the FIELDRUK (Household Identifier). The same level of attention has not been given to the other identifiers that are included in the data base, the CHILDID (Person identifier) and the _IDHD01 (Household identifier). These identifiers have been created for the public files and can also be found in the master files by default. The PERSRUK should be used to link records between files and the FIELDRUK to determine the household when using the master files.

    Release date: 2004-10-05

  • Surveys and statistical programs – Documentation: 56F0003X
    Description:

    This electronic product is a comprehensive reference tool that contains an inventory of surveys, conducted by Statistics Canada, used to measure household/individual Internet use. Product features include survey names; descriptions (including information such as objective of survey, sample size, frequency, target group and response rate); user guides; charts and graphs. Also included is an extremely useful Questionnaire Comparability Chart that displays common content among questionnaires. This is a useful source of background information for respondents, researchers and those involved in survey development and questionnaire design.

    Release date: 2004-09-23

  • Surveys and statistical programs – Documentation: 62F0026M2004001
    Description:

    This report describes the quality indicators produced for the 2002 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.

    Release date: 2004-09-15

  • Surveys and statistical programs – Documentation: 92-390-X
    Description:

    This report includes a definition of the 2001 place of work concept and the place of work geography, standard text on data collection and coverage (including data collection methods, special coverage studies, sampling and weighting, edit and follow-up, coverage and content considerations). Both standard and subject-matter specific text pieces are also included for data assimilation (automated as well as interactive coding), edit and imputation and data evaluation. Finally, this technical report includes a section on historical comparability.

    Release date: 2004-08-26

  • Surveys and statistical programs – Documentation: 81-595-M2004020
    Geography: Canada
    Description:

    This article discusses the collection and interpretation of statistical data on Canada's trade in culture goods. It defines the products that are included in culture trade and explains how appropriate products are selected from the relevant classification standards.

    This version has been replaced by Culture Goods Trade Data User Guide, Catalogue No. 81-595-MIE2006040.

    Release date: 2004-07-28

  • Surveys and statistical programs – Documentation: 92-388-X
    Description:

    This report contains basic conceptual and data quality information to help users interpret and make use of census occupation data. It gives an overview of the collection, coding (to the 2001 National Occupational Classification), edit and imputation of the occupation data from the 2001 Census. The report describes procedural changes between the 2001 and earlier censuses, and provides an analysis of the quality level of the 2001 Census occupation data. Finally, it details the revision of the 1991 Standard Occupational Classification used in the 1991 and 1996 Censuses to the 2001 National Occupational Classification for Statistics used in 2001. The historical comparability of data coded to the two classifications is discussed. Appendices to the report include a table showing historical data for the 1991, 1996 and 2001 Censuses.

    Release date: 2004-07-15
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