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All (3) ((3 results))

  • 1. Relative Performance of Methods Based on Model-Assisted Survey Regression Estimation Archived
    Articles and reports: 11-522-X202100100009
    Description:

    Use of auxiliary data to improve the efficiency of estimators of totals and means through model-assisted survey regression estimation has received considerable attention in recent years. Generalized regression (GREG) estimators, based on a working linear regression model, are currently used in establishment surveys at Statistics Canada and several other statistical agencies.  GREG estimators use common survey weights for all study variables and calibrate to known population totals of auxiliary variables. Increasingly, many auxiliary variables are available, some of which may be extraneous. This leads to unstable GREG weights when all the available auxiliary variables, including interactions among categorical variables, are used in the working linear regression model. On the other hand, new machine learning methods, such as regression trees and lasso, automatically select significant auxiliary variables and lead to stable nonnegative weights and possible efficiency gains over GREG.  In this paper, a simulation study, based on a real business survey sample data set treated as the target population, is conducted to study the relative performance of GREG, regression trees and lasso in terms of efficiency of the estimators.

    Key Words: Model assisted inference; calibration estimation; model selection; generalized regression estimator.

    Release date: 2021-10-29
  • 2. Projections of the Indigenous populations and households in Canada, 2016 to 2041: Overview of data sources, methods, assumptions and scenarios
    Articles and reports: 17-20-00012021001
    Description:

    This document briefly describes the methods and data sources used in the preparation of the projections of the Indigenous populations and households in Canada for the period 2016 to 2041, produced using the Demosim microsimulation projection model. It also includes a description of the assumptions and scenarios that were selected for this projection exercise.

    Release date: 2021-10-06
  • 3. The 2021 Revisions of the Labour Force Survey (LFS) Archived
    Surveys and statistical programs – Documentation: 71F0031X2021001
    Description:

    This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2021. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 2016 Census and includes updates to 2016 Geography classification system.

    Release date: 2021-01-25
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Analysis (2)

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  • 1. Relative Performance of Methods Based on Model-Assisted Survey Regression Estimation Archived
    Articles and reports: 11-522-X202100100009
    Description:

    Use of auxiliary data to improve the efficiency of estimators of totals and means through model-assisted survey regression estimation has received considerable attention in recent years. Generalized regression (GREG) estimators, based on a working linear regression model, are currently used in establishment surveys at Statistics Canada and several other statistical agencies.  GREG estimators use common survey weights for all study variables and calibrate to known population totals of auxiliary variables. Increasingly, many auxiliary variables are available, some of which may be extraneous. This leads to unstable GREG weights when all the available auxiliary variables, including interactions among categorical variables, are used in the working linear regression model. On the other hand, new machine learning methods, such as regression trees and lasso, automatically select significant auxiliary variables and lead to stable nonnegative weights and possible efficiency gains over GREG.  In this paper, a simulation study, based on a real business survey sample data set treated as the target population, is conducted to study the relative performance of GREG, regression trees and lasso in terms of efficiency of the estimators.

    Key Words: Model assisted inference; calibration estimation; model selection; generalized regression estimator.

    Release date: 2021-10-29
  • 2. Projections of the Indigenous populations and households in Canada, 2016 to 2041: Overview of data sources, methods, assumptions and scenarios
    Articles and reports: 17-20-00012021001
    Description:

    This document briefly describes the methods and data sources used in the preparation of the projections of the Indigenous populations and households in Canada for the period 2016 to 2041, produced using the Demosim microsimulation projection model. It also includes a description of the assumptions and scenarios that were selected for this projection exercise.

    Release date: 2021-10-06
Reference (1)

Reference (1) ((1 result))

  • 1. The 2021 Revisions of the Labour Force Survey (LFS) Archived
    Surveys and statistical programs – Documentation: 71F0031X2021001
    Description:

    This paper introduces and explains modifications made to the Labour Force Survey estimates in January 2021. Some of these modifications include the adjustment of all LFS estimates to reflect population counts based on the 2016 Census and includes updates to 2016 Geography classification system.

    Release date: 2021-01-25
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