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All (26,490)

All (26,490) (0 to 10 of 26,490 results)

  • 1. Employment characteristics for persons with and without disabilities, annual - Open in new window/tab
    Table: 14-10-0479-01
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Annual
    Description: Employment estimates by class of worker, province, gender, age group and disability, annual.
    Release date: 2026-05-19
  • 2. Employment by industry for persons with and without disabilities, annual - Open in new window/tab
    Table: 14-10-0479-02
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Annual
    Description: Employment estimates by North American Industry Classification System (NAICS), province, gender, age group and disability, annual.
    Release date: 2026-05-19
  • 3. Employment by occupation for persons with and without disabilities, annual - Open in new window/tab
    Table: 14-10-0479-03
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Annual
    Description: Employment estimates by National Occupational Classification (NOC), province, gender, age group and disability, annual.
    Release date: 2026-05-19
  • 4. Employment by job tenure for persons with and without disabilities, annual - Open in new window/tab
    Table: 14-10-0479-04
    Geography: Canada, Geographical region of Canada, Province or territory
    Frequency: Annual
    Description: Employment estimates by job tenure, province, gender, age group and disability, annual.
    Release date: 2026-05-19
  • 5. Building permits March 2026 - Open in new window/tab
    Stats in brief: 11-001-X20261393592
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2026-05-19
  • 6. Consumer Price Index April 2026 - Open in new window/tab
    Stats in brief: 11-001-X20261393665
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2026-05-19
  • 7. Consumer Price Index Data Visualization Tool - Open in new window/tab
    Data Visualization: 71-607-X2018016
    Description: This interactive dashboard provides access to current and historical Consumer Price Index (CPI) data in a dynamic and customizable format. Key indicators such as the 12-month and 1-month inflation rates and price trends are presented in interactive charts, allowing users to compare and analyze price changes of all the goods and services in the CPI basket over time as well as across geography (national, provincial and territorial levels).

    Other CPI indicators available in this tool include the Bank of Canada’s core measures of inflation, seasonally adjusted inflation rates, and CPI basket weights.

    This web-based application is updated monthly, as soon as the data for the latest reference month is released in The Daily.

    Release date: 2026-05-19
  • 8. New Housing Price Index: Interactive Dashboard - Open in new window/tab
    Data Visualization: 71-607-X2019013
    Description: This web application provides access to new housing prices data for Canada and 27 census metropolitan areas (CMA). The maps, charts and tables draw from information collected from respondents who provide information on Canada's new housing prices. The interactive dashboard allows users to visualize statistics on new housing prices' monthly and annual movements and on rankings by CMAs of the largest monthly price movements.
    Release date: 2026-05-19
  • 9. Wholesale and Retail Services Price Indexes: Interactive Tool - Open in new window/tab
    Data Visualization: 71-607-X2019015
    Description: This dashboard highlights the latest data for the Wholesale Services Price Index (WSPI) and the Retail Services Price Index (RSPI). The WSPI and the RSPI are indicators of change in the price of wholesaling and retailing services in Canada. This price is defined as a margin, which is the difference between the selling price and the purchase price of products sold. With this tool, data users can explore current and historical trends for various types of wholesaling and retailing services. Key indicators such as the latest quarterly and year-over-year (annual) changes, as well as services price trends are presented in interactive charts, allowing users to compare and analyze services price changes over time for different types of services. The interactive tool also allows users to rank subsectors based on their relative importance (2013 weights) to the overall Canadian wholesale or retail sector . This web-based application is updated quarterly, as soon as data for the latest reference period are released in The Daily.
    Release date: 2026-05-19
  • 10. Building permits: Interactive Dashboard - Open in new window/tab
    Data Visualization: 71-607-X2021005
    Description: Building permits: Interactive Dashboard can be used to visualize monthly data or trend analysis of the value of permits issued by Canadian municipalities as well as monthly changes on residential units created. The user can view those data by selecting reference period, geography, type of building structure and value type for seasonal adjustment.
    Release date: 2026-05-19
Data (13,239)

Data (13,239) (70 to 80 of 13,239 results)

Analysis (10,752)

Analysis (10,752) (200 to 210 of 10,752 results)

  • 201. Estimating monthly indicators for Consumer Confidence using Structural Time Series Models - Open in new window/tab
    Articles and reports: 12-001-X202500200003
    Description: In this paper a model-based inference procedure based on a multivariate structural time series model is developed for the production of monthly figures about consumer confidence. The input for the model are five series of direct estimates for the indices that measure consumer confidence, which are derived from the Dutch Consumer Survey. The model improves the accuracy of the direct estimates, since it provides a better separation of measurement errors and sampling errors from estimated target parameters. The standard errors for the month-to-month changes are clearly smaller under the time series model. A second problem addressed in this paper is related to the transition to a new survey process in 2017. Structural time series models in combination with a parallel run are applied to estimate discontinuities induced by the redesign. An algorithm designed for the consumer confidence variables is developed to construct uninterrupted input series for the aforementioned structural time series model. This inference method facilitated a smooth transition to a new survey design and resulted in uninterrupted series about consumer confidence that date back to 1986. The method is implemented for the production of official monthly figures on consumer confidence in the Netherlands.
    Release date: 2025-12-23
  • 202. Collinearity diagnostics in generalized linear models fitted with survey data - Open in new window/tab
    Articles and reports: 12-001-X202500200004
    Description: The class of generalized linear models (GLM) is a flexible generalization of ordinary least squares regression that allows the linear model to be related to the response variable via a link function and assumes the magnitude of the variance of each measurement to be a function of its predicted value. Multicollinearity in GLMs can inflate variances of the estimated coefficients and cause poor prediction in certain regions of the regression space. It may also cause a nonsignificant Wald statistic even when the predictors are highly predictive in a model of the family of GLMs. Little previous research has closely investigated the diagnostics of multicollinearity in GLMs, especially when complex survey data are used. In this paper, we develop variance inflation factors (VIFs) that measure the amount that the variance of a parameter estimator is increased due to multicollinearity in GLMs. We also extend VIFs and condition indexes to apply to complex survey data, accounting for design features, e.g. weights, clusters, and strata. Illustrations of these methods are given using data from a household survey of health and nutrition.
    Release date: 2025-12-23
  • 203. Quantile balancing inverse probability weighting for non-probability samples - Open in new window/tab
    Articles and reports: 12-001-X202500200005
    Description: The use of non-probability data sources for statistical purposes and for official statistics has become increasingly popular in recent years. However, statistical inference based on non-probability samples is made more difficult by nature of their biasedness and lack of representativity. In this paper we propose quantile balancing inverse probability weighting estimator (QBIPW) for non-probability samples. We apply the idea of Harms and Duchesne (2006) allowing the use of quantile information in the estimation process to reproduce known totals and the distribution of auxiliary variables. We discuss the estimation of the QBIPW probabilities and its variance. Our simulation study has demonstrated that the proposed estimators are robust against model mis-specification and, as a result, help to reduce bias and mean squared error. Finally, we applied the proposed methods to estimate the share of job vacancies aimed at Ukrainian workers in Poland using an integrated set of administrative and survey data about job vacancies.
    Release date: 2025-12-23
  • 204. Quality indicators for representation in administrative data - Open in new window/tab
    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
  • 205. Integrating probability and non-probability samples through deep learning-based mass imputation - Open in new window/tab
    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
  • 206. Generalized regression estimation under misspecified sample design - Open in new window/tab
    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
  • 207. Improved small area inference from data integration using global-local priors - Open in new window/tab
    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
  • 208. Performance of hierarchical Bayes small area estimators using noninformative and informative priors with an application to the Canadian Labor Force Survey - Open in new window/tab
    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
  • 209. Approximate hierarchical Bayes small area estimation using Natural Exponential Family with Quadratic Variance Function and poststratification - Open in new window/tab
    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
  • 210. Modified observed best prediction strategies for small area estimation with unit-level data - Open in new window/tab
    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
Reference (2,027)

Reference (2,027) (50 to 60 of 2,027 results)

  • 51. Report on content changes for the 2026 Census of Population: Sexual orientation - Open in new window/tab
    Surveys and statistical programs – Documentation: 98-20-00052026003
    Description: This report outlines the steps taken to develop a new question capturing data on sexual orientation for the 2026 Census of Population questionnaire.
    Release date: 2025-07-04
  • 52. 2024 Census Test: Design and methodology of the content test - Open in new window/tab
    Surveys and statistical programs – Documentation: 98-20-00052026004
    Description: This report provides detailed insight into the design and methodology of the content test component of the 2024 Census Test. This test evaluated changes to the wording and flow of some questions, as well as the potential addition of new questions, to help determine the content of the 2026 Census of Population.
    Release date: 2025-07-04
  • 53. 2026 Census Content Fact Sheets - Open in new window/tab
    Surveys and statistical programs – Documentation: 98-20-0004
    Description: This series of fact sheets offers a concise overview of changes in content for the 2026 Census of Population questionnaire by topic.
    Release date: 2025-07-04
  • 54. Technical Reports on Changes for the 2026 Census - Open in new window/tab
    Surveys and statistical programs – Documentation: 98-20-0005
    Description: This series of reports provides an in-depth look at changes in content for the 2026 Census of Population questionnaire as well as detailed information on the design and methodology of the content test component of the 2024 Census Test. The reports explain the conceptual frameworks and definitions used and outline the related findings from the 2024 Census Test on sexual orientation, homelessness and general health.
    Release date: 2025-07-04
  • 55. User Guide and Data Dictionary for the Dataset on Confirmed Cases of COVID-19 - Open in new window/tab
    Surveys and statistical programs – Documentation: 13-26-0002
    Description: Created in collaboration with the Public Health Agency of Canada (PHAC), this user guide with appended data dictionary provides Canadians and researchers with required information to be able to utilize the Detailed preliminary information on confirmed cases of COVID-19 (Revised) table.

    The user guide with appended data dictionary describes background information of COVID-19 as well as objectives, coverage, content, limitations and data quality concerns of the table.

    Release date: 2025-07-02
  • 56. Canadian Census Health and Environment Cohort: User Guide - Open in new window/tab
    Surveys and statistical programs – Documentation: 13-26-0005
    Description: The Canadian Census Health and Environment Cohorts (CanCHECs) are a series of population-based microdata linkages. The CanCHECs combine census respondents to the long-form questionnaire with administrative health data and annual postal codes for mailing addresses. These data can be used to examine health outcomes by population characteristics measured by the census long-form sample data. This user guide has been created to help potential data users, including researchers and academics, public health officials, government agencies, the private sector, and non-governmental organizations.
    Release date: 2025-06-18
  • 57. Census Subdivision Boundary File, Reference Guide - Open in new window/tab
    Geographic files and documentation: 92-162-G
    Description: This reference guide is intended for users of the Census Subdivisions Boundary File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.
    Release date: 2025-06-18
  • 58. Census Subdivision Boundary File - Open in new window/tab
    Geographic files and documentation: 92-162-X
    Description: The Census Subdivision Boundary File contains the boundaries of all census subdivisions which combined cover all of Canada. A census subdivision is a municipality or an area treated as an equivalent to a municipality for statistical purposes (for example, unorganized territories). The file provides a framework for mapping and spatial analysis using commercially available geographic information systems (GIS) or other mapping software.

    The Census Subdivision Boundary File is portrayed in Lambert conformal conic projection and is based on the North American Datum of 1983 (NAD83). A reference guide is available (92-162-G).

    Release date: 2025-06-18
  • 59. Road Network File, Reference Guide - Open in new window/tab
    Geographic files and documentation: 92-500-G
    Description: This reference guide is intended for users of the Census of Population Road Network File (92-500-X). It provides an overview of the general methodology used to create this file, as well as important technical information.
    Release date: 2025-06-18
  • 60. Road Network File - Open in new window/tab
    Geographic files and documentation: 92-500-X
    Geography: Canada
    Description:

    This geographical file represents Canada's national road network, containing information such as street names, types, directions and address ranges.

    A reference guide is available (Road Network File, Reference Guide, 92-500-G).
    Release date: 2025-06-18
Other (1)

Other (1) ((1 result))

  • 1. Data Visualization: Best Practices - Open in new window/tab
    89-26-0005
    Description: This document provides best practices in data visualization for basic charts. A data visualization product can be created with very different goals and for different audiences with a wide range of expertise. General information applicable to any data visualization product is provided, as well as detailed information for data visualization by chart. This report covers 5 different categories of charts, and presents graphs from the following 5 general categories: pie charts, bar charts, point charts, line charts and maps.
    Release date: 2023-02-24

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