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All (136)
All (136) (0 to 10 of 136 results)
- Surveys and statistical programs – Documentation: 11-633-X2025004Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 40 years.Release date: 2025-12-08
- Journals and periodicals: 11-522-XDescription: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.Release date: 2025-09-08
- Articles and reports: 12-001-X202500100009Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.Release date: 2025-06-30
- 4. Comments by Risto Lehtonen on “Progress in survey science and practice: Yesterday-today-tomorrow”Articles and reports: 12-001-X202500100018Description: In his article, Professor Carl-Erik Särndal presents for sample-based statistics a new conceptual framework with only a few key assumptions. Selected aspects of the research tradition in Survey Science are briefly discussed in my comments.Release date: 2025-06-30
- Surveys and statistical programs – Documentation: 98-303-XDescription: The Coverage Technical Report will present the errors included in census data that result from persons who are either missed (not enumerated) or enumerated more than once. The population coverage error is one of the most important types of errors because it affects the accuracy of not only population counts, but also all the census data results that describe the characteristics of the population universe.Release date: 2024-10-23
- Articles and reports: 12-001-X202400100010Description: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.Release date: 2024-06-25
- Articles and reports: 75F0002M2024005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.Release date: 2024-04-26
- 8. ABS DataLab output checking tools ArchivedArticles and reports: 11-522-X202200100006Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.Release date: 2024-03-25
- Surveys and statistical programs – Documentation: 32-26-0007Description: Census of Agriculture data provide statistical information on farms and farm operators at fine geographic levels and for small subpopulations. Quality evaluation activities are essential to ensure that census data are reliable and that they meet user needs. This report provides data quality information pertaining to the Census of Agriculture, such as sources of error, error detection, disclosure control methods, data quality indicators, response rates and collection rates.Release date: 2024-02-06
- Articles and reports: 11-633-X2023003Description: This paper spans the academic work and estimation strategies used in national statistics offices. It addresses the issue of producing fine, grid-level geography estimates for Canada by exploring the measurement of subprovincial and subterritorial gross domestic product using Yukon as a test case.Release date: 2023-12-15
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Analysis (94)
Analysis (94) (0 to 10 of 94 results)
- Journals and periodicals: 11-522-XDescription: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.Release date: 2025-09-08
- Articles and reports: 12-001-X202500100009Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.Release date: 2025-06-30
- 3. Comments by Risto Lehtonen on “Progress in survey science and practice: Yesterday-today-tomorrow”Articles and reports: 12-001-X202500100018Description: In his article, Professor Carl-Erik Särndal presents for sample-based statistics a new conceptual framework with only a few key assumptions. Selected aspects of the research tradition in Survey Science are briefly discussed in my comments.Release date: 2025-06-30
- Articles and reports: 12-001-X202400100010Description: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.Release date: 2024-06-25
- Articles and reports: 75F0002M2024005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.Release date: 2024-04-26
- 6. ABS DataLab output checking tools ArchivedArticles and reports: 11-522-X202200100006Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.Release date: 2024-03-25
- Articles and reports: 11-633-X2023003Description: This paper spans the academic work and estimation strategies used in national statistics offices. It addresses the issue of producing fine, grid-level geography estimates for Canada by exploring the measurement of subprovincial and subterritorial gross domestic product using Yukon as a test case.Release date: 2023-12-15
- Articles and reports: 75F0002M2023005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.Release date: 2023-08-29
- 9. Data Quality as Fitness for Use ArchivedStats in brief: 89-20-00062023001Description: This course is intended for Government of Canada employees who would like to learn about evaluating the quality of data for a particular use. Whether you are a new employee interested in learning the basics, or an experienced subject matter expert looking to refresh your skills, this course is here to help.Release date: 2023-07-17
- Articles and reports: 98-20-00012021003Description:
This fact sheet provides a concise description of the context to the understanding of confidence intervals. Confidence intervals are a useful data quality indicator. Confidence intervals will usually be available in data tables accessible through the Statistics Canada website.
Release date: 2022-09-21
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Reference (42)
Reference (42) (20 to 30 of 42 results)
- Surveys and statistical programs – Documentation: 81-595-M2007056Geography: CanadaDescription: This handbook discusses the collection and interpretation of statistical data on Canada's trade in culture services.Release date: 2007-10-31
- 22. Quality Assurance Review: Summary Report ArchivedSurveys and statistical programs – Documentation: 12-594-XDescription:
This Summary Report provides an overview of the findings of a Quality Assurance Review that was conducted for nine key statistical programs during the period September 2006 to February 2007. The review was commissioned by Statistics Canada's Policy Committee in order to assess the soundness of quality assurance processes for these nine programs and to propose improvements where needed. The Summary Report describes the principal themes that recur frequently throughout these programs, as well as providing guidance for future reviews of this type.
Release date: 2007-06-20 - Surveys and statistical programs – Documentation: 62F0026M2005006Description:
This report describes the quality indicators produced for the 2003 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2005-10-06 - Surveys and statistical programs – Documentation: 89-552-M2005013Geography: CanadaDescription:
This report documents key aspects of the development of the International Adult Literacy and Life Skills Survey (ALL) - its theoretical roots, the domains selected for possible assessment, the approaches taken to assessment in each domain and the criteria that were employed to decide which domains were to be carried in the final design. As conceived, the ALL survey was meant to build on the success of the International Adult Literacy Survey (IALS) assessments by extending the range of skills assessed and by improving the quality of the assessment methods employed. This report documents several successes including: · the development of a new framework and associated robust measures for problem solving · the development of a powerful numeracy framework and associated robust measures · the specification of frameworks for practical cognition, teamwork and information and communication technology literacy The report also provides insight into those domains where development failed to yield approaches to assessment of sufficient quality, insight that reminds us that scientific advance in this domain is hard won.
Release date: 2005-03-24 - Surveys and statistical programs – Documentation: 62F0026M2004003Geography: Province or territoryDescription:
This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households.
This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the statistics that can be created using expenditure data (e.g., budget share, market share and aggregates).
Release date: 2004-12-13 - Surveys and statistical programs – Documentation: 13-604-M2004045Description:
How "good" are the National Tourism Indicators (NTI)? How can their quality be measured? This study looks to answer these questions by analysing the revisions to the NTI estimates for the period 1997 through 2001.
Release date: 2004-10-25 - Surveys and statistical programs – Documentation: 62F0026M2004001Description:
This report describes the quality indicators produced for the 2002 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2004-09-15 - Surveys and statistical programs – Documentation: 92-390-XDescription:
This report includes a definition of the 2001 place of work concept and the place of work geography, standard text on data collection and coverage (including data collection methods, special coverage studies, sampling and weighting, edit and follow-up, coverage and content considerations). Both standard and subject-matter specific text pieces are also included for data assimilation (automated as well as interactive coding), edit and imputation and data evaluation. Finally, this technical report includes a section on historical comparability.
Release date: 2004-08-26 - Surveys and statistical programs – Documentation: 81-595-M2004020Geography: CanadaDescription:
This article discusses the collection and interpretation of statistical data on Canada's trade in culture goods. It defines the products that are included in culture trade and explains how appropriate products are selected from the relevant classification standards.
This version has been replaced by Culture Goods Trade Data User Guide, Catalogue No. 81-595-MIE2006040.
Release date: 2004-07-28 - Surveys and statistical programs – Documentation: 62F0026M2003001Description:
This report describes the quality indicators produced for the 2001 Survey of Household Spending. It covers the usual quality indicators that help users interpret the data, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates.
Release date: 2003-11-26