Analysis

Skip to filters. View results.

What’s new on our website

View results

Filter results by

Search Help
Currently selected filters that can be removed
Remove Remove "12-001-x" filterRemove Remove "1992" filterRemove Remove "R" filter
Clear all

Keyword(s)

Subject

Year of publication

1 facets displayed. 1 facets selected.

Author(s)

5 facets displayed. 1 facets selected.
Sort Help
entries

Results

All (4)

All (4) ((4 results))

  • 1. Some recent work on resampling methods for complex surveys Archived
    Articles and reports: 12-001-X199200214486
    Description:

    Resampling methods for inference with complex survey data include the jackknife, balanced repeated replication (BRR) and the bootstrap. We review some recent work on these methods for standard error and confidence interval estimation. Some empirical results for non-smooth statistics are also given.

    Release date: 1992-12-15
  • 2. Robustness and optimal design under prediction models for finite populations Archived
    Articles and reports: 12-001-X199200214488
    Description:

    In many finite population sampling problems the design that is optimal in the sense of minimizing the variance of the best linear unbiased estimator under a particular working model is bad in the sense of robustness - it leaves the estimator extremely vulnerable to bias if the working model is incorrect. However there are some important models under which one design provides both efficiency and robustness. We present a theorem that identifies such models and their optimal designs.

    Release date: 1992-12-15
  • 3. A variation of the housing unit method for estimating the population of small, rural areas: A case study of the local expert procedure Archived
    Articles and reports: 12-001-X199200114493
    Description:

    This paper examines the suitability of a survey-based procedure for estimating populations in small, rural areas. The procedure is a variation of the Housing Unit Method. It employs the use of local experts enlisted to provide information about the demographic characteristics of households randomly selected from residential unit sample frames developed from utility records. The procedure is nonintrusive and less costly than traditional survey data collection efforts. Because the procedure is based on random sampling, confidence intervals can be constructed around the population estimated by the technique. The results of a case study are provided in which the total population is estimated for three unincorporated communities in rural, southern Nevada.

    Release date: 1992-06-15
  • 4. A comparison of some estimators of a set of population totals Archived
    Articles and reports: 12-001-X199200114496
    Description:

    The Population Estimates Program of Statistics Canada has traditionally been benchmarked to the most recent census, with no allowance for census coverage error. Because of a significant increase in the level of undercoverage in the 1986 Census, however, Statistics Canada is considering the possibility of adjusting the base population of the estimates program for net census undercoverage. This paper develops and compares four estimators of such a base population: the unadjusted census counts, the adjusted census counts, a preliminary test estimator, and a composite estimator. A generalization of previously-proposed risk functions, known as the Weighted Mean Square Error (WMSE), is used as the basis of comparison. The WMSE applies not only to population totals, but to functions of population totals such as population shares and growth rates between censuses. The use of the WMSE to develop and evaluate small-area estimators in the context of census adjustment is also described.

    Release date: 1992-06-15
Stats in brief (0)

Stats in brief (0) (0 results)

No content available at this time.

Articles and reports (4)

Articles and reports (4) ((4 results))

  • 1. Some recent work on resampling methods for complex surveys Archived
    Articles and reports: 12-001-X199200214486
    Description:

    Resampling methods for inference with complex survey data include the jackknife, balanced repeated replication (BRR) and the bootstrap. We review some recent work on these methods for standard error and confidence interval estimation. Some empirical results for non-smooth statistics are also given.

    Release date: 1992-12-15
  • 2. Robustness and optimal design under prediction models for finite populations Archived
    Articles and reports: 12-001-X199200214488
    Description:

    In many finite population sampling problems the design that is optimal in the sense of minimizing the variance of the best linear unbiased estimator under a particular working model is bad in the sense of robustness - it leaves the estimator extremely vulnerable to bias if the working model is incorrect. However there are some important models under which one design provides both efficiency and robustness. We present a theorem that identifies such models and their optimal designs.

    Release date: 1992-12-15
  • 3. A variation of the housing unit method for estimating the population of small, rural areas: A case study of the local expert procedure Archived
    Articles and reports: 12-001-X199200114493
    Description:

    This paper examines the suitability of a survey-based procedure for estimating populations in small, rural areas. The procedure is a variation of the Housing Unit Method. It employs the use of local experts enlisted to provide information about the demographic characteristics of households randomly selected from residential unit sample frames developed from utility records. The procedure is nonintrusive and less costly than traditional survey data collection efforts. Because the procedure is based on random sampling, confidence intervals can be constructed around the population estimated by the technique. The results of a case study are provided in which the total population is estimated for three unincorporated communities in rural, southern Nevada.

    Release date: 1992-06-15
  • 4. A comparison of some estimators of a set of population totals Archived
    Articles and reports: 12-001-X199200114496
    Description:

    The Population Estimates Program of Statistics Canada has traditionally been benchmarked to the most recent census, with no allowance for census coverage error. Because of a significant increase in the level of undercoverage in the 1986 Census, however, Statistics Canada is considering the possibility of adjusting the base population of the estimates program for net census undercoverage. This paper develops and compares four estimators of such a base population: the unadjusted census counts, the adjusted census counts, a preliminary test estimator, and a composite estimator. A generalization of previously-proposed risk functions, known as the Weighted Mean Square Error (WMSE), is used as the basis of comparison. The WMSE applies not only to population totals, but to functions of population totals such as population shares and growth rates between censuses. The use of the WMSE to develop and evaluate small-area estimators in the context of census adjustment is also described.

    Release date: 1992-06-15
Journals and periodicals (0)

Journals and periodicals (0) (0 results)

No content available at this time.

Report a problem or mistake on this page
Date modified:

Search help

How do I use the filters and the search box?

  • You can initiate a search by entering keywords or selecting filters (e.g., under Subject, Geography, etc.) on the left side of the page.

  • Filters can be used together or in any combination. Each time you select a filter, the results on the page are updated.

  • To start a new search, click on the Clear all button above the search box or deselect each filter.

  • Specified keywords and filters appear above the search box. You can deselect any or all the tags to refine or clear your search.

How do I refine my search?

  • You can enter keywords in the search box. It is not necessary to use “+” or “, “ or “AND”.

  • You can delete some or all of the keywords from your search string.

  • Quotes around keywords limit the search to a specific phrase.

    • For example, “labour force survey” will limit results to products containing this phrase.

  • Use “or” between keywords to obtain results that contain one or more search terms.

    • For example, labour or­ force or survey will limit results to products containing any or all of these words.

How does the search work?

  • This search looks for results that have your query term in the title, description, subject, geography, product number or other information about the product.

    • For example, when searching the term ‘Diseases’, all results with the word ‘Diseases’ in the title, description or tagged the subject appear.

  • The text within an article or publication are not searched. For full text searching of articles, use the site search.

Sort help

How are the results ordered?

The Sort by feature provides three options:

  • By date – sorts results by product release date starting with the most recent.
  • By relevance is only needed or beneficial when you use the search box and submit a search query. Results are ordered by a combination of where the search term appears in the content, e.g., if it appears in the title, it likely means the product is more relevant to your search; how up to date or new the content in the product is; how popular the product is; and other factors.
  • By title – sorts results alphabetically.

Sort help

How are the results ordered?

The Sort by feature provides four options:

  • By date – sorts results by product release date starting with the most recent.
  • By most popular – gives priority to results that are most frequently selected by users, followed by the most recent.
  • By relevance is only needed or beneficial when you use the search box and submit a search query. Results are ordered by a combination of where the search term appears in the content, e.g., if it appears in the title, it likely means the product is more relevant to your search; how up to date or new the content in the product is; how popular the product is; and other factors.
  • By title – sorts results alphabetically.