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- Articles and reports: 12-001-X202400100011Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.Release date: 2024-06-25
- Stats in brief: 11-627-M2021092Description:
This infographic provides a high-level overview of Statistics Canada’s Disaggregated Data Action Plan, which will produce detailed statistical information on specific population groups. This plan is essential to highlight the lived experiences of diverse groups of people in Canada, such as women, Indigenous peoples, racialized populations and people living with disabilities.
Release date: 2021-12-08 - Articles and reports: 12-001-X201100211606Description:
This paper introduces a U.S. Census Bureau special compilation by presenting four other papers of the current issue: three papers from authors Tillé, Lohr and Thompson as well as a discussion paper from Opsomer.
Release date: 2011-12-21 - 4. Census coverage error: A demographic evaluation ArchivedArticles and reports: 12-001-X20000015177Description:
The 1996 Canadian Census is adjusted for coverage error as estimated primarily through the Reverse Record Check (RRC). In this paper, we will show how there is a wealth of additional information from the 1996 Reverse Record Check of direct value to population estimation. Beyond its ability to estimate coverage error, it is possible to extend the Reverse Record Check classification results to obtain an alternative estimate of demographic growth - potentially decomposed by component. This added feature of the Reverse Record Check provides promise in the evaluation of estimated census coverage error as well as insight as to possible problems in the estimation of selected components in the population estimates program.
Release date: 2000-08-30 - 5. Combining census, survey, demographic and administrative data to produce a one number census ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015638Description:
The focus of Symposium'99 is on techniques and methods for combining data from different sources and on analysis of the resulting data sets. In this talk we illustrate the usefulness of taking such an "integrating" approach when tackling a complex statistical problem. The problem itself is easily described - it is how to approximate, as closely as possible, a "perfect census", and in particular, how to obtain census counts that are "free" of underenumeration. Typically, underenumeration is estimated by carrying out a post enumeration survey (PES) following the census. In the UK in 1991 the PEF failed to identify the full size of the underenumeration and so demographic methods were used to estimate the extent of the undercount. The problems with the "traditional" PES approach in 1991 resulted in a joint research project between the Office for National Statistics and the Department of Social Statistics at the University of Southampton aimed at developing a methodology which will allow a "One Number Census" in the UK in 2001. That is, underenumeration will be accounted for not just at high levels of aggregation, but right down to the lowest levels at which census tabulations are produced. In this way all census outputs will be internally consistent, adding to the national population estimates. The basis of this methodology is the integration of information from a number of data sources in order to achieve this "One Number".
Release date: 2000-03-02 - Articles and reports: 91F0015M1998005Geography: CanadaDescription:
All countries that organize censuses have concerns about data quality and coverage error. Different methods have been developed in evaluating the quality of census data and census undercount. Some methods make use of information independent of the census itself, while some others are designed to check the internal consistency of the data. These are expensive and complicated operations.
Given that the population in each country is organized differently and that the administrative structures differ from one country to another, no universal method can be applied. In order to compare the methods and identify their strengths and gaps, Demography Division of Statistics Canada has reviewed the procedures used in four industrialized countries: the United States, the United Kingdom, Australia and, of course, Canada. It appears from this review that demographic analysis can help considerably in the identification of inconsistencies through comparisons of consecutive censuses, while micro-level record linkage and survey based procedures are essential in order to estimate the number of people omitted or counted twice in census collection. The most important conclusion from this review is that demographers and statisticians have to work together in order to evaluate the figures the accuracy of which will always remain questionable.
Release date: 1998-03-27
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Analysis (5)
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- Articles and reports: 12-001-X202400100011Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.Release date: 2024-06-25
- Stats in brief: 11-627-M2021092Description:
This infographic provides a high-level overview of Statistics Canada’s Disaggregated Data Action Plan, which will produce detailed statistical information on specific population groups. This plan is essential to highlight the lived experiences of diverse groups of people in Canada, such as women, Indigenous peoples, racialized populations and people living with disabilities.
Release date: 2021-12-08 - Articles and reports: 12-001-X201100211606Description:
This paper introduces a U.S. Census Bureau special compilation by presenting four other papers of the current issue: three papers from authors Tillé, Lohr and Thompson as well as a discussion paper from Opsomer.
Release date: 2011-12-21 - 4. Census coverage error: A demographic evaluation ArchivedArticles and reports: 12-001-X20000015177Description:
The 1996 Canadian Census is adjusted for coverage error as estimated primarily through the Reverse Record Check (RRC). In this paper, we will show how there is a wealth of additional information from the 1996 Reverse Record Check of direct value to population estimation. Beyond its ability to estimate coverage error, it is possible to extend the Reverse Record Check classification results to obtain an alternative estimate of demographic growth - potentially decomposed by component. This added feature of the Reverse Record Check provides promise in the evaluation of estimated census coverage error as well as insight as to possible problems in the estimation of selected components in the population estimates program.
Release date: 2000-08-30 - Articles and reports: 91F0015M1998005Geography: CanadaDescription:
All countries that organize censuses have concerns about data quality and coverage error. Different methods have been developed in evaluating the quality of census data and census undercount. Some methods make use of information independent of the census itself, while some others are designed to check the internal consistency of the data. These are expensive and complicated operations.
Given that the population in each country is organized differently and that the administrative structures differ from one country to another, no universal method can be applied. In order to compare the methods and identify their strengths and gaps, Demography Division of Statistics Canada has reviewed the procedures used in four industrialized countries: the United States, the United Kingdom, Australia and, of course, Canada. It appears from this review that demographic analysis can help considerably in the identification of inconsistencies through comparisons of consecutive censuses, while micro-level record linkage and survey based procedures are essential in order to estimate the number of people omitted or counted twice in census collection. The most important conclusion from this review is that demographers and statisticians have to work together in order to evaluate the figures the accuracy of which will always remain questionable.
Release date: 1998-03-27
Reference (1)
Reference (1) ((1 result))
- 1. Combining census, survey, demographic and administrative data to produce a one number census ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015638Description:
The focus of Symposium'99 is on techniques and methods for combining data from different sources and on analysis of the resulting data sets. In this talk we illustrate the usefulness of taking such an "integrating" approach when tackling a complex statistical problem. The problem itself is easily described - it is how to approximate, as closely as possible, a "perfect census", and in particular, how to obtain census counts that are "free" of underenumeration. Typically, underenumeration is estimated by carrying out a post enumeration survey (PES) following the census. In the UK in 1991 the PEF failed to identify the full size of the underenumeration and so demographic methods were used to estimate the extent of the undercount. The problems with the "traditional" PES approach in 1991 resulted in a joint research project between the Office for National Statistics and the Department of Social Statistics at the University of Southampton aimed at developing a methodology which will allow a "One Number Census" in the UK in 2001. That is, underenumeration will be accounted for not just at high levels of aggregation, but right down to the lowest levels at which census tabulations are produced. In this way all census outputs will be internally consistent, adding to the national population estimates. The basis of this methodology is the integration of information from a number of data sources in order to achieve this "One Number".
Release date: 2000-03-02
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