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All (5)

All (5) ((5 results))

  • 1. Wastewater-based estimates of cannabis and drug use in Canada: Analytical methods and supplementary information
    Articles and reports: 13-605-X201900100011
    Description:

    This document is a supplement to The Daily article, Wastewater-based estimates of cannabis and drug use in Canada: Pilot-Test Results (citation). It describes the data analysis supporting the results of the article, including the statistical testing and the treatment of outliers and missing data. Additionally, for each of the parameters required to estimate drug consumption, the document provides the values and uncertainty that were used and references to the literature supporting those values.

    Release date: 2019-08-26
  • 2. Closing remarks of the Symposium 2005: Methodological Challenges for Future Information Needs Archived
    Articles and reports: 11-522-X20050019600
    Description:

    Closing remarks

    Release date: 2007-03-02
  • 3. Model-based unemployment rate estimation for the Canadian Labour Force Survey: A hierarchical Bayes approach Archived
    Articles and reports: 12-001-X20030016602
    Description:

    The Canadian Labour Force Survey (LFS) produces monthly direct estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for subprovincial areas such as census metropolitan areas (CMAs) and census agglomerations (CAs). However, for some subprovincial areas, the direct estimates are not very reliable since the sample size in some areas is quite small. In this paper, a cross-sectional and time-series model is used to borrow strength across areas and time periods to produce model-based unemployment rate estimates for CMAs and CAs. This model is a generalization of a widely used cross-sectional model in small area estimation and includes a random walk or AR(1) model for the random time component. Monthly Employment Insurance (EI) beneficiary data at the CMA or CA level are used as auxiliary covariates in the model. A hierarchical Bayes (HB) approach is employed and the Gibbs sampler is used to generate samples from the joint posterior distribution. Rao-Blackwellized estimators are obtained for the posterior means and posterior variances of the CMA/CA-level unemployment rates. The HB method smoothes the survey estimates and leads to a substantial reduction in standard errors. Base on posterior distributions, bayesian model fitting is also investigated in this paper.

    Release date: 2003-07-31
  • 4. Regression composite estimation for the Canadian Labour Force Survey: Evaluation and implementation Archived
    Articles and reports: 12-001-X20010015855
    Description:

    The Canadian Labour Force Survey (LFS) is a monthly survey with a complex rotating panel design. After extensive studies, including the investigation of a number of alternative methods for exploiting the sample overlap to improve the quality of estimates, the LFS has chosen a composite estimation method which achieves this goal while satisfying practical constraints. In addition, for variables where there is a substantial gain in efficiency, the new time series tend to make more sense from a subject-matter perspective. This makes it easier to explain LFS estimates to users and the media. Because of the reduced variance under composite estimation, for some variables it is now possible to publish monthly estimates where only three-month moving averages were published in the past. In addition, a greater number of series can be successfully seasonally adjusted.

    Release date: 2001-08-22
  • 5. Issues and strategies for small area data Archived
    Articles and reports: 12-001-X199400114436
    Description:

    This paper identifies some technical issues in the provision of small area data derived from censuses, administrative records and surveys. Although the issues are of a general nature, they are discussed in the context of programs at Statistics Canada. For survey-based estimates, the need for developing an overall strategy is stressed and salient features of survey design that have an impact on small area data are highlighted in the context of redesigning a household survey. A brief review of estimation methods with their strengths and weaknesses is also presented.

    Release date: 1994-06-15
Stats in brief (0)

Stats in brief (0) (0 results)

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Articles and reports (5)

Articles and reports (5) ((5 results))

  • 1. Wastewater-based estimates of cannabis and drug use in Canada: Analytical methods and supplementary information
    Articles and reports: 13-605-X201900100011
    Description:

    This document is a supplement to The Daily article, Wastewater-based estimates of cannabis and drug use in Canada: Pilot-Test Results (citation). It describes the data analysis supporting the results of the article, including the statistical testing and the treatment of outliers and missing data. Additionally, for each of the parameters required to estimate drug consumption, the document provides the values and uncertainty that were used and references to the literature supporting those values.

    Release date: 2019-08-26
  • 2. Closing remarks of the Symposium 2005: Methodological Challenges for Future Information Needs Archived
    Articles and reports: 11-522-X20050019600
    Description:

    Closing remarks

    Release date: 2007-03-02
  • 3. Model-based unemployment rate estimation for the Canadian Labour Force Survey: A hierarchical Bayes approach Archived
    Articles and reports: 12-001-X20030016602
    Description:

    The Canadian Labour Force Survey (LFS) produces monthly direct estimates of the unemployment rate at national and provincial levels. The LFS also releases unemployment estimates for subprovincial areas such as census metropolitan areas (CMAs) and census agglomerations (CAs). However, for some subprovincial areas, the direct estimates are not very reliable since the sample size in some areas is quite small. In this paper, a cross-sectional and time-series model is used to borrow strength across areas and time periods to produce model-based unemployment rate estimates for CMAs and CAs. This model is a generalization of a widely used cross-sectional model in small area estimation and includes a random walk or AR(1) model for the random time component. Monthly Employment Insurance (EI) beneficiary data at the CMA or CA level are used as auxiliary covariates in the model. A hierarchical Bayes (HB) approach is employed and the Gibbs sampler is used to generate samples from the joint posterior distribution. Rao-Blackwellized estimators are obtained for the posterior means and posterior variances of the CMA/CA-level unemployment rates. The HB method smoothes the survey estimates and leads to a substantial reduction in standard errors. Base on posterior distributions, bayesian model fitting is also investigated in this paper.

    Release date: 2003-07-31
  • 4. Regression composite estimation for the Canadian Labour Force Survey: Evaluation and implementation Archived
    Articles and reports: 12-001-X20010015855
    Description:

    The Canadian Labour Force Survey (LFS) is a monthly survey with a complex rotating panel design. After extensive studies, including the investigation of a number of alternative methods for exploiting the sample overlap to improve the quality of estimates, the LFS has chosen a composite estimation method which achieves this goal while satisfying practical constraints. In addition, for variables where there is a substantial gain in efficiency, the new time series tend to make more sense from a subject-matter perspective. This makes it easier to explain LFS estimates to users and the media. Because of the reduced variance under composite estimation, for some variables it is now possible to publish monthly estimates where only three-month moving averages were published in the past. In addition, a greater number of series can be successfully seasonally adjusted.

    Release date: 2001-08-22
  • 5. Issues and strategies for small area data Archived
    Articles and reports: 12-001-X199400114436
    Description:

    This paper identifies some technical issues in the provision of small area data derived from censuses, administrative records and surveys. Although the issues are of a general nature, they are discussed in the context of programs at Statistics Canada. For survey-based estimates, the need for developing an overall strategy is stressed and salient features of survey design that have an impact on small area data are highlighted in the context of redesigning a household survey. A brief review of estimation methods with their strengths and weaknesses is also presented.

    Release date: 1994-06-15
Journals and periodicals (0)

Journals and periodicals (0) (0 results)

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