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All (2,481) (20 to 30 of 2,481 results)

  • 21. Improved small area inference from data integration using global-local priors
    Articles and reports: 12-001-X202500200009
    Description: We present and apply methodology to improve inference for small area parameters by using data from several sources. This work extends Cahoy and Sedransk (2023) who showed how to integrate summary statistics from several sources. Our methodology uses hierarchical global-local prior distributions to make inferences for the proportion of individuals in Florida’s counties who do not have health insurance. Results from an extensive simulation study show that this methodology will provide improved inference by using several data sources. Among the five model variants evaluated the ones using horseshoe priors for all variances have better performance than the ones using lasso priors for the local variances.
    Release date: 2025-12-23
  • 22. Performance of hierarchical Bayes small area estimators using noninformative and informative priors with an application to the Canadian Labor Force Survey
    Articles and reports: 12-001-X202500200010
    Description: In this paper, we study the performance of hierarchical Bayes (HB) small area estimators using noninformative and informative priors. We apply the Bayesian models of You and Chapman (2006) and You (2021) to the Canadian Labor Force Survey (LFS) data and evaluate the impact of the priors on the HB estimators. A Bayesian model comparison and simulation study are also conducted. Our results indicate that a correct informative prior can lead to very good results, and noninformative priors can also perform very well. Incorrect informative priors can lead to poor results in terms of large bias and large coefficient of variation (CV). Noninformative priors are recommended in practice for HB small area estimation unless correctly specified informative priors are available. Informative priors are particularly useful when the number of small areas is relatively small.
    Release date: 2025-12-23
  • 23. Approximate hierarchical Bayes small area estimation using Natural Exponential Family with Quadratic Variance Function and poststratification
    Articles and reports: 12-001-X202500200011
    Description: We propose an approximate hierarchical Bayes approach that uses the Natural Exponential Family with Quadratic Variance Function (NEF-QVF) in combining information from multiple sources to improve traditional survey estimates of finite population means for small areas. Unlike other Bayesian approaches in finite population sampling, we do not assume a model for all units of the finite population and do not require linking sampled units to the finite population frame. We assume a model only for the finite population units in which the outcome variable is observed; because, for these units, the assumed model can be checked using existing statistical tools. We do not posit an elaborate model on the true means for unobserved units. Instead, we assume that population means of cells with the same combination of factor levels are identical across small areas, and that the population mean for a cell is identical to the mean of the observed units in that cell. We apply our proposed methodology to a real-life survey, linking information from multiple disparate data sources. We also provide practical ways of model selection that can be applied to a wider class of models under similar setting but for a diverse range of scientific problems.
    Release date: 2025-12-23
  • 24. Modified observed best prediction strategies for small area estimation with unit-level data
    Articles and reports: 12-001-X202500200012
    Description: The observed best prediction (OBP) under a nested-error regression (NER) model was previously proposed using a design-based mean squared prediction error (MSPE) as a tool to derive the best predictive estimator (BPE). A recent study showed the OBP under the NER model may suffer from numerical instability when computing the BPE. We propose several modifications of the OBP under the NER model, including ones using a model-based MSPE to derive the BPE, to improve the numerical stability and predictive performance. We compare the performance of the modified OBP strategies with the existing methods in a simulation study. A real-data example is discussed.
    Release date: 2025-12-23
  • 25. Sampling for business surveys at Statistics Canada
    Articles and reports: 12-001-X202500200013
    Description: This article examines the methodological complexities associated with the design of business surveys, with particular emphasis on sampling strategies implemented by National Statistical Offices (NSOs). It addresses the inherent challenges posed by the dynamic nature of the business population, which necessitates continual updates to the sampling frame to ensure representativeness and relevance. Critical design considerations include the determination of optimal sample sizes, stratification across key dimensions such as industry, geographic region, and enterprise size, as well as the treatment of business births and the exclusion of inactive (or “dead”) units. The article applies Bankier’s (1988) power allocation method to a two-way stratification scheme defined by industry and geography, evaluating its performance by comparing the resulting coefficients of variation with those obtained via a raking algorithm applied to the marginal coefficients. Furthermore, the approach is extended to a multivariate context to accommodate multiple estimation domains. The discussion also encompasses practical issues related to sample rotation and coordination, which are critical for maintaining data quality and minimizing respondent burden over time.
    Release date: 2025-12-23
  • 26. Survey Methodology
    Journals and periodicals: 12-001-X
    Geography: Canada
    Description: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.
    Release date: 2025-12-23
  • 27. Modelling the Impact of Immigration on Student Numbers
    Articles and reports: 11-633-X2025005
    Description: This study presents an approach to model changes in the numbers of elementary, secondary and postsecondary students who are immigrants (including both permanent residents and non permanent residents) in response to changes in overall immigration levels.
    Release date: 2025-12-22
  • 28. National Address Register
    Profile of a community or region: 46-26-0002
    Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.
    Release date: 2025-12-19
  • 29. Technical Guide on Demographic Estimates at Statistics Canada
    Surveys and statistical programs – Documentation: 91-528-X
    Description: The Technical Guide on Demographic Estimates at Statistics Canada provides detailed descriptions of the most current data sources and methods used by the Centre for demography at Statistics Canada to produce demographic estimates as part of the Demographic estimates program. They comprise postcensal and intercensal population estimates; base population; births and deaths; immigrants; emigrants; returning emigrants; non-permanent residents; interprovincial migration; subprovincial estimates of population and intraprovincial migration; population estimates by age and gender; and census family estimates. A glossary of commonly used terms is available at the end of the guide.
    Release date: 2025-12-17
  • 30. Fighting Misinformation
    Stats in brief: 89-20-00062025001
    Description: This video is designed to help you critically assess the data presented to you. No data is perfect. By understanding the strengths and limitations of the data, you can avoid being misled—and make smarter, more informed decisions.
    Release date: 2025-12-15
Data (10)

Data (10) ((10 results))

  • 1. Social Policy Simulation Database and Model (SPSD/M)
    Public use microdata: 89F0002X
    Description: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.
    Release date: 2026-02-12
  • 2. National Address Register
    Profile of a community or region: 46-26-0002
    Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.
    Release date: 2025-12-19
  • 3. PASSAGES microsimulation model
    Table: 89-26-0006
    Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.
    Release date: 2025-03-12
  • 4. Canadian Statistical Geospatial Explorer Hub Archived
    Data Visualization: 71-607-X2020010
    Description: The Canadian Statistical Geospatial Explorer empowers users to discover geo enabled data holdings of Statistics Canada at various levels of geography including at the neighbourhood level. Users are able to visualize, thematically map, spatially explore and analyze, export and consume data in various formats. Users can also view the data superimposed on satellite imagery, topographic and street layers.
    Release date: 2024-08-21
  • 5. Income divergence index (D-index) by census tract
    Table: 11-10-0074-01
    Geography: Census tract
    Frequency: Occasional
    Description:

    The divergence index (D-index) describes the degree that families with different income levels are mixing together in neighbourhoods. It compares neighbourhood (census tract, CT) discrete income distributions to a base distribution, which is the income quintiles of the neighbourhood’s census metropolitan area (CMA).

    Release date: 2020-06-22
  • 6. Housing Data Viewer Archived
    Data Visualization: 71-607-X2019010
    Description: The Housing Data Viewer is a visualization tool that allows users to explore Statistics Canada data on a map. Users can use the tool to navigate, compare and export data.
    Release date: 2019-10-30
  • 7. Findings of the Canadian Vehicle Fuel Pilot Survey Archived
    Table: 53-500-X
    Description:

    This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.

    Release date: 2004-10-21
  • 8. National Tourism Indicators, Historical Estimates Archived
    Table: 13-220-X
    Description: In the 1997 edition, new and revised benchmarks were introduced for 1992 and 1988. The indicators are used to monitor supply, demand and employment for tourism in Canada on a timely basis. The annual tables are derived using the National Income and Expenditure Accounts (NIEA) and various industry and travel surveys. Tables providing actual data and percentage changes, for seasonally adjusted current and constant price estimates are included. In addition, an analytical section provides graphs, and time series of first differences, percentage changes, and seasonal factors for selected indicators. Data are published from 1987 and the publication will be available on the day of release. New data are included in the demand tables for non-tourism commodities produced by non-tourism industries and in the employment tables covering direct tourism employment generated by non-tourism industries. This product was commissioned by the Canadian Tourism Commission to provide annual updates for the Tourism Satellite Account.
    Release date: 2003-01-08
  • 9. Historical Statistics of Canada Archived
    Table: 11-516-X
    Description:

    The second edition of Historical statistics of Canada was jointly produced by the Social Science Federation of Canada and Statistics Canada in 1983. This volume contains about 1,088 statistical tables on the social, economic and institutional conditions of Canada from the start of Confederation in 1867 to the mid-1970s. The tables are arranged in sections with an introduction explaining the content of each section, the principal sources of data for each table, and general explanatory notes regarding the statistics. In most cases, there is sufficient description of the individual series to enable the reader to use them without consulting the numerous basic sources referenced in the publication.

    The electronic version of this historical publication is accessible on the Internet site of Statistics Canada as a free downloadable document: text as HTML pages and all tables as individual spreadsheets in a comma delimited format (CSV) (which allows online viewing or downloading).

    Release date: 1999-07-29
  • 10. National Population Health Survey Overview Archived
    Table: 82-567-X
    Description:

    The National Population Health Survey (NPHS) is designed to enhance the understanding of the processes affecting health. The survey collects cross-sectional as well as longitudinal data. In 1994/95 the survey interviewed a panel of 17,276 individuals, then returned to interview them a second time in 1996/97. The response rate for these individuals was 96% in 1996/97. Data collection from the panel will continue for up to two decades. For cross-sectional purposes, data were collected for a total of 81,000 household residents in all provinces (except people on Indian reserves or on Canadian Forces bases) in 1996/97.

    This overview illustrates the variety of information available by presenting data on perceived health, chronic conditions, injuries, repetitive strains, depression, smoking, alcohol consumption, physical activity, consultations with medical professionals, use of medications and use of alternative medicine.

    Release date: 1998-07-29
Analysis (2,037)

Analysis (2,037) (10 to 20 of 2,037 results)

  • 11. Quality indicators for representation in administrative data
    Articles and reports: 12-001-X202500200006
    Description: National Statistical Institutes (NSIs) are directing resources into advancing the use of administrative data in official statistics. Administrative data, however, are not developed for the purpose of producing statistics rather as a result of an event or transaction relating to administrative procedures of organizations, public administrations and government agencies. Therefore, it is essential to check the quality of the administrative data with respect to sources of error, particularly representativeness to the target population. In this paper, we utilize the strength of probability-based reference samples or censuses that can be used to detect the lack of representativeness in administrative data and introduce quality indicators based on distance metrics and representativity indicators (R-indicators). We demonstrate their application with a simulation study and discuss a real application applied on a UK Office for National Statistics (ONS) administrative dataset.
    Release date: 2025-12-23
  • 12. Integrating probability and non-probability samples through deep learning-based mass imputation
    Articles and reports: 12-001-X202500200007
    Description: Although probability samples have been regarded as the gold standard to collect information for population-based study, non-probability samples have been used frequently in practice due to low cost, convenience, and the lack of the sampling frame for the survey. Naïve estimates based on non-probability samples without any adjustments may be misleading due to selection bias. Recently, a valid data integration approach that includes mass imputation, propensity score weighting, and calibration has been used to improve the representativeness of non-probability samples. The effectiveness of the mass imputation approach depends on the underlying model assumptions. In this paper, we propose using deep learning for the mass imputation in the combining of probability and non-probability samples and compare it with several modern machine learning-based mass imputation approaches, including generalized additive modeling, regression tree, random forest, and XG-boosting. In the simulation study, deep learning-based approaches have been shown to be more robust and effective than other mass imputation approaches against the failure of underlying model assumptions under non-linearity scenarios.
    Release date: 2025-12-23
  • 13. Generalized regression estimation under misspecified sample design
    Articles and reports: 12-001-X202500200008
    Description: Classical design-based survey estimation relies on a properly specified sampling design for valid inference. We consider the properties of regression estimation under a misspecified sample design, in which the nominal and true inclusion probabilities do not necessarily match. This general misspecified sample design setting encompasses many challenges in the modern survey environment. Under this setting, an asymptotic analysis of the regression estimator, an expression of the bias, and an expression of the variance are presented. Further, a consistent variance estimator is derived and an expression which estimates the bias in-part or in-whole is discussed. This later expression may be used as an indicator of the presence of bias due to misspecification by a practitioner. A simulation study is conducted to support the presented theory.
    Release date: 2025-12-23
  • 14. Improved small area inference from data integration using global-local priors
    Articles and reports: 12-001-X202500200009
    Description: We present and apply methodology to improve inference for small area parameters by using data from several sources. This work extends Cahoy and Sedransk (2023) who showed how to integrate summary statistics from several sources. Our methodology uses hierarchical global-local prior distributions to make inferences for the proportion of individuals in Florida’s counties who do not have health insurance. Results from an extensive simulation study show that this methodology will provide improved inference by using several data sources. Among the five model variants evaluated the ones using horseshoe priors for all variances have better performance than the ones using lasso priors for the local variances.
    Release date: 2025-12-23
  • 15. Performance of hierarchical Bayes small area estimators using noninformative and informative priors with an application to the Canadian Labor Force Survey
    Articles and reports: 12-001-X202500200010
    Description: In this paper, we study the performance of hierarchical Bayes (HB) small area estimators using noninformative and informative priors. We apply the Bayesian models of You and Chapman (2006) and You (2021) to the Canadian Labor Force Survey (LFS) data and evaluate the impact of the priors on the HB estimators. A Bayesian model comparison and simulation study are also conducted. Our results indicate that a correct informative prior can lead to very good results, and noninformative priors can also perform very well. Incorrect informative priors can lead to poor results in terms of large bias and large coefficient of variation (CV). Noninformative priors are recommended in practice for HB small area estimation unless correctly specified informative priors are available. Informative priors are particularly useful when the number of small areas is relatively small.
    Release date: 2025-12-23
  • 16. Approximate hierarchical Bayes small area estimation using Natural Exponential Family with Quadratic Variance Function and poststratification
    Articles and reports: 12-001-X202500200011
    Description: We propose an approximate hierarchical Bayes approach that uses the Natural Exponential Family with Quadratic Variance Function (NEF-QVF) in combining information from multiple sources to improve traditional survey estimates of finite population means for small areas. Unlike other Bayesian approaches in finite population sampling, we do not assume a model for all units of the finite population and do not require linking sampled units to the finite population frame. We assume a model only for the finite population units in which the outcome variable is observed; because, for these units, the assumed model can be checked using existing statistical tools. We do not posit an elaborate model on the true means for unobserved units. Instead, we assume that population means of cells with the same combination of factor levels are identical across small areas, and that the population mean for a cell is identical to the mean of the observed units in that cell. We apply our proposed methodology to a real-life survey, linking information from multiple disparate data sources. We also provide practical ways of model selection that can be applied to a wider class of models under similar setting but for a diverse range of scientific problems.
    Release date: 2025-12-23
  • 17. Modified observed best prediction strategies for small area estimation with unit-level data
    Articles and reports: 12-001-X202500200012
    Description: The observed best prediction (OBP) under a nested-error regression (NER) model was previously proposed using a design-based mean squared prediction error (MSPE) as a tool to derive the best predictive estimator (BPE). A recent study showed the OBP under the NER model may suffer from numerical instability when computing the BPE. We propose several modifications of the OBP under the NER model, including ones using a model-based MSPE to derive the BPE, to improve the numerical stability and predictive performance. We compare the performance of the modified OBP strategies with the existing methods in a simulation study. A real-data example is discussed.
    Release date: 2025-12-23
  • 18. Sampling for business surveys at Statistics Canada
    Articles and reports: 12-001-X202500200013
    Description: This article examines the methodological complexities associated with the design of business surveys, with particular emphasis on sampling strategies implemented by National Statistical Offices (NSOs). It addresses the inherent challenges posed by the dynamic nature of the business population, which necessitates continual updates to the sampling frame to ensure representativeness and relevance. Critical design considerations include the determination of optimal sample sizes, stratification across key dimensions such as industry, geographic region, and enterprise size, as well as the treatment of business births and the exclusion of inactive (or “dead”) units. The article applies Bankier’s (1988) power allocation method to a two-way stratification scheme defined by industry and geography, evaluating its performance by comparing the resulting coefficients of variation with those obtained via a raking algorithm applied to the marginal coefficients. Furthermore, the approach is extended to a multivariate context to accommodate multiple estimation domains. The discussion also encompasses practical issues related to sample rotation and coordination, which are critical for maintaining data quality and minimizing respondent burden over time.
    Release date: 2025-12-23
  • 19. Survey Methodology
    Journals and periodicals: 12-001-X
    Geography: Canada
    Description: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.
    Release date: 2025-12-23
  • 20. Modelling the Impact of Immigration on Student Numbers
    Articles and reports: 11-633-X2025005
    Description: This study presents an approach to model changes in the numbers of elementary, secondary and postsecondary students who are immigrants (including both permanent residents and non permanent residents) in response to changes in overall immigration levels.
    Release date: 2025-12-22
Reference (382)

Reference (382) (380 to 390 of 382 results)

  • 381. Household Survey Frame Service - Global Positioning System (GPS) and digital mapping pilot test
    Surveys and statistical programs – Documentation: 5241
    Description: The SRGD is conducting a Global Positioning System (GPS) and digital mapping test to improve Statistic Canada's rural dwelling inventory by collecting dwelling identifiers to be used by field collection staff. In rural areas dwelling identification can be difficult where there is an absence of civic style addresses. The test is evaluating alternative methods for dwelling identification including the collection of GPS coordinates and digital photos using a mapping application and a digital tablet
  • 382. Respondent Selection Study for the General Social Survey
    Surveys and statistical programs – Documentation: 8014
    Description: This study will be used to determine which method would be the most effective to select households in Canada for any given survey that is conducted by Statistics Canada.

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