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All (4) ((4 results))

  • 1. Canadian Survey on Disability, 2022: Concepts and Methods Guide
    Surveys and statistical programs – Documentation: 89-654-X2023004
    Description: The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem. The 2022 CSD Concepts and Methods Guide is designed to assist CSD data users by providing relevant information on survey content and concepts, sampling design, collection methods, data processing, data quality and product availability.
    Release date: 2023-12-01
  • 2. Sampling and Weighting Technical Report, Census of Population
    Surveys and statistical programs – Documentation: 98-306-X
    Description:

    This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

    Release date: 2023-10-04
  • 3. Agriculture–Population Linkage: Data quality report
    Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25
  • 4. Sampling with adaptive drawing probabilities
    Articles and reports: 12-001-X202300100009
    Description: In this paper, with and without-replacement versions of adaptive proportional to size sampling are presented. Unbiased estimators are developed for these methods and their properties are studied. In the two versions, the drawing probabilities are adapted during the sampling process based on the observations already selected. To this end, in the version with-replacement, after each draw and observation of the variable of interest, the vector of the auxiliary variable will be updated using the observed values of the variable of interest to approximate the exact selection probability proportional to size. For the without-replacement version, first, using an initial sample, we model the relationship between the variable of interest and the auxiliary variable. Then, utilizing this relationship, we estimate the unknown (unobserved) population units. Finally, on these estimated population units, we select a new sample proportional to size without-replacement. These approaches can significantly improve the efficiency of designs not only in the case of a positive linear relationship, but also in the case of a non-linear or negative linear relationship between the variables. We investigate the efficiencies of the designs through simulations and real case studies on medicinal flowers, social and economic data.
    Release date: 2023-06-30
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  • 1. Sampling with adaptive drawing probabilities
    Articles and reports: 12-001-X202300100009
    Description: In this paper, with and without-replacement versions of adaptive proportional to size sampling are presented. Unbiased estimators are developed for these methods and their properties are studied. In the two versions, the drawing probabilities are adapted during the sampling process based on the observations already selected. To this end, in the version with-replacement, after each draw and observation of the variable of interest, the vector of the auxiliary variable will be updated using the observed values of the variable of interest to approximate the exact selection probability proportional to size. For the without-replacement version, first, using an initial sample, we model the relationship between the variable of interest and the auxiliary variable. Then, utilizing this relationship, we estimate the unknown (unobserved) population units. Finally, on these estimated population units, we select a new sample proportional to size without-replacement. These approaches can significantly improve the efficiency of designs not only in the case of a positive linear relationship, but also in the case of a non-linear or negative linear relationship between the variables. We investigate the efficiencies of the designs through simulations and real case studies on medicinal flowers, social and economic data.
    Release date: 2023-06-30
Reference (3)

Reference (3) ((3 results))

  • 1. Canadian Survey on Disability, 2022: Concepts and Methods Guide
    Surveys and statistical programs – Documentation: 89-654-X2023004
    Description: The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem. The 2022 CSD Concepts and Methods Guide is designed to assist CSD data users by providing relevant information on survey content and concepts, sampling design, collection methods, data processing, data quality and product availability.
    Release date: 2023-12-01
  • 2. Sampling and Weighting Technical Report, Census of Population
    Surveys and statistical programs – Documentation: 98-306-X
    Description:

    This report describes sampling, weighting and estimation procedures used in the Census of Population. It provides operational and theoretical justifications for them, and presents the results of the evaluations of these procedures.

    Release date: 2023-10-04
  • 3. Agriculture–Population Linkage: Data quality report
    Surveys and statistical programs – Documentation: 32-26-0006
    Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
    Release date: 2023-08-25
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