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  • 1. A portrait of military families in Canada from the 2021 Census
    Articles and reports: 75-006-X202500100001
    Description: Using data collected for the first time in 50 years from the 2021 Census of Population on current and past military service in the Canadian Armed Forces, this study examines key sociodemographic characteristics of the families of currently serving members and Veterans. It also takes a closer look at less studied military families, such as Veteran families, one-parent families, same-gender couple families and dual-serving couple families.
    Release date: 2025-01-13
  • 2. Military families in Canada
    Stats in brief: 11-627-M2025001
    Description: This infographic provides a portrait of military families in Canada, of both serving members and Veterans.
    Release date: 2025-01-13
  • 3. The outlook of rural businesses, fourth quarter of 2024
    Articles and reports: 21-006-X2025001
    Description: This article examines the business conditions and expectations of rural and small town businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, fourth quarter of 2024.
    Release date: 2025-01-13
  • 4. Study: A portrait of military families in Canada from the 2021 Census
    Stats in brief: 11-001-X202501338929
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2025-01-13
  • 5. Statistics Canada - Infographics
    Journals and periodicals: 11-627-M
    Description: Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

    These infographics will provide a quick overview of Statistics Canada survey data.

    Release date: 2025-01-13
  • 6. Rural and Small Town Canada Analysis Bulletin
    Journals and periodicals: 21-006-X
    Geography: Canada
    Description: This series of analytical articles provides insights on the socio-economic environment in rural communities in Canada. New articles will be released periodically.
    Release date: 2025-01-13
  • 7. Insights on Canadian Society
    Journals and periodicals: 75-006-X
    Geography: Canada
    Description: This publication brings together and analyzes a wide range of data sources in order to provide information on various aspects of Canadian society, including labour, income, education, social, and demographic issues, that affect the lives of Canadians.
    Release date: 2025-01-13
  • 8. Leading indicator of international arrivals to Canada December 2024
    Stats in brief: 11-001-X202501027643
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2025-01-10
  • 9. Labour Force Survey December 2024
    Stats in brief: 11-001-X20250103587
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2025-01-10
  • 10. Building permits November 2024
    Stats in brief: 11-001-X20250103592
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2025-01-10
Stats in brief (2,723)

Stats in brief (2,723) (0 to 10 of 2,723 results)

Articles and reports (7,125)

Articles and reports (7,125) (0 to 10 of 7,125 results)

  • 1. A portrait of military families in Canada from the 2021 Census
    Articles and reports: 75-006-X202500100001
    Description: Using data collected for the first time in 50 years from the 2021 Census of Population on current and past military service in the Canadian Armed Forces, this study examines key sociodemographic characteristics of the families of currently serving members and Veterans. It also takes a closer look at less studied military families, such as Veteran families, one-parent families, same-gender couple families and dual-serving couple families.
    Release date: 2025-01-13
  • 2. The outlook of rural businesses, fourth quarter of 2024
    Articles and reports: 21-006-X2025001
    Description: This article examines the business conditions and expectations of rural and small town businesses in Canada, with comparison to urban counterparts by industry for contextual support. Topics include business obstacles, expectations for the next year, workforce changes and other subjects from the Canadian Survey on Business Conditions, fourth quarter of 2024.
    Release date: 2025-01-13
  • 3. Workforce Insights: Demographics in the publishing industries subsector, 2015 to 2023
    Articles and reports: 11-621-M2025002
    Description: This paper leverages administrative data to examine the distribution of the workforce by gender, age and full-time work status from 2015 to 2023 for the newspaper, periodical, and book publishers industries.
    Release date: 2025-01-09
  • 4. Exploring a skewness conjecture: Expanding Cochran’s rule to a proportion estimated from a complex sample
    Articles and reports: 12-001-X202400200001
    Description: Cochran’s rule states that a standard (Wald) two-sided 95% confidence interval around a sample mean drawn from a population with positive skewness is reasonable when the sample size is greater than 25 times the square of the skewness coefficient of the population. We investigate whether a variant of this crude rule applies for a proportion estimated from a stratified simple random sample.
    Release date: 2024-12-20
  • 5. Daily rhythm of data quality: Evidence from the Survey of Unemployed Workers in New Jersey
    Articles and reports: 12-001-X202400200002
    Description: This paper investigates whether survey data quality fluctuates over the day. After laying out the argument theoretically, panel data from the Survey of Unemployed Workers in New Jersey are analyzed. Several indirect indicators of response error are investigated, including item nonresponse, interview completion time, rounding, and measures of the quality of time diary data. The evidence that we assemble for a time of day of interview effect is weak or nonexistent. Item nonresponse and the probability that interview completion time is among the 5% shortest appear to increase in the evening, but a more thorough assessment requires instrumental variables.
    Release date: 2024-12-20
  • 6. Recursive Neyman algorithm for optimum sample allocation under box constraints on sample sizes in strata
    Articles and reports: 12-001-X202400200003
    Description: The optimum sample allocation in stratified sampling is one of the basic issues of survey methodology. It is a procedure of dividing the overall sample size into strata sample sizes in such a way that for given sampling designs in strata the variance of the stratified \pi estimator of the population total (or mean) for a given study variable assumes its minimum. In this work, we consider the optimum allocation of a sample, under lower and upper bounds imposed jointly on sample sizes in strata. We are concerned with the variance function of some generic form that, in particular, covers the case of the simple random sampling without replacement in strata. The goal of this paper is twofold. First, we establish (using the Karush-Kuhn-Tucker conditions) a generic form of the optimal solution, the so-called optimality conditions. Second, based on the established optimality conditions, we derive an efficient recursive algorithm, named RNABOX, which solves the allocation problem under study. The RNABOX can be viewed as a generalization of the classical recursive Neyman allocation algorithm, a popular tool for optimum allocation when only upper bounds are imposed on sample strata-sizes. We implement RNABOX in R as a part of our package stratallo which is available from the Comprehensive R Archive Network (CRAN) repository.
    Release date: 2024-12-20
  • 7. Bayesian predictive inference of a finite population mean without specifying the relation between the study variable and the covariates
    Articles and reports: 12-001-X202400200004
    Description: While we avoid specifying the parametric relationship between the study variable and covariates, we illustrate the advantage of including a spatial component to better account for the covariates in our models to make Bayesian predictive inference. We treat each unique covariate combination as an individual stratum, then we use small area estimation techniques to make inference about the finite population mean of the continuous response variable. The two spatial models used are the conditional autoregressive and simple conditional autoregressive models. We include the spatial effects by creating the adjacency matrix via the Mahalanobis distance between covariates. We also show how to incorporate survey weights into the spatial models when dealing with probability survey data. We compare the results of two non-spatial models including the Scott-Smith model and the Battese, Harter, and Fuller model to the spatial models. We illustrate the comparison between the aforementioned models with an application using BMI data from eight counties in California. Our goal is to have neighboring strata yield similar predictions, and to increase the difference between strata that are not neighbors. Ultimately, using the spatial models shows less global pooling compared to the non-spatial models, which was the desired outcome.
    Release date: 2024-12-20
  • 8. Robust adaptive survey design for time changes in mixed-mode response propensities
    Articles and reports: 12-001-X202400200005
    Description: Adaptive survey designs (ASDs) tailor recruitment protocols to population subgroups that are relevant to a survey. In recent years, effective ASD optimization has been the topic of research and several applications. However, the performance of an optimized ASD over time is sensitive to time changes in response propensities. How adaptation strategies can adjust to such variation over time is not yet fully understood. In this paper, we propose a robust optimization approach in the context of sequential mixed-mode surveys employing Bayesian analysis. The approach is formulated as a mathematical programming problem that explicitly accounts for uncertainty due to time change. ASD decisions can then be made by considering time-dependent variation in conditional mode response propensities and between-mode correlations in response propensities. The approach is demonstrated using a case study: the 2014-2017 Dutch Health Survey. We evaluate the sensitivity of ASD performance to 1) the budget level and 2) the length of applicable historic time-series data. We find there is only a moderate dependence on the budget level and the dependence on historic data is moderated by the amount of seasonality during the year.
    Release date: 2024-12-20
  • 9. Investigating mode effects in interviewer variances using two representative multi-mode surveys
    Articles and reports: 12-001-X202400200006
    Description: As mixed-mode designs become increasingly popular, their effects on data quality have attracted much scholarly attention. Most studies focused on the bias properties of mixed-mode designs; few of them have investigated whether mixed-mode designs have heterogeneous variance structures across modes. While many characteristics of mixed-mode designs, such as varied interviewer usage, systematic differences in respondents, varying levels of social desirability bias, among others, may lead to heterogeneous variances in mode-specific point estimates of population means, this study specifically investigates whether interviewer variances remain consistent across different modes in mixed-mode studies. To address this research question, we utilize data collected from two distinct study designs. In the first design, when interviewers are responsible for either face-to-face or telephone mode, we examine whether there are mode differences in interviewer variances for 1) sensitive political questions, 2) international items, 3) and item missing indicators on international items, using the Arab Barometer wave 6 Jordan data. In the second design, we draw on Health and Retirement Study (HRS) 2016 core survey data to examine the question on three topics when interviewers are responsible for both modes. The topics cover 1) the CESD depression scale, 2) interviewer observations, and 3) the physical activity scale. To account for the lack of interpenetrated designs in both data sources, we include respondent-level covariates in our models. We find significant differences in interviewer variances on one item (twelve items in total) in the Arab Barometer study; whereas for HRS, the results are three out of eighteen. Overall, we find the magnitude of the interviewer variances larger in FTF than TEL on sensitive items. We conduct simulations to understand the power to detect mode effects in the typically modest interviewer sample sizes.
    Release date: 2024-12-20
  • 10. Fully synthetic data for complex surveys
    Articles and reports: 12-001-X202400200008
    Description: When seeking to release public use files for confidential data, statistical agencies can generate fully synthetic data. We propose an approach for making fully synthetic data from surveys collected with complex sampling designs. Our approach adheres to the general strategy proposed by Rubin (1993). Specifically, we generate pseudo-populations by applying the weighted finite population Bayesian bootstrap to account for survey weights, take simple random samples from those pseudo-populations, estimate synthesis models using these simple random samples, and release simulated data drawn from the models as public use files. To facilitate variance estimation, we use the framework of multiple imputation with two data generation strategies. In the first, we generate multiple data sets from each simple random sample. In the second, we generate a single synthetic data set from each simple random sample. We present multiple imputation combining rules for each setting. We illustrate the repeated sampling properties of the combining rules via simulation studies, including comparisons with synthetic data generation based on pseudo-likelihood methods. We apply the proposed methods to a subset of data from the American Community Survey.
    Release date: 2024-12-20
Journals and periodicals (321)

Journals and periodicals (321) (0 to 10 of 321 results)

  • 1. Statistics Canada - Infographics
    Journals and periodicals: 11-627-M
    Description: Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

    These infographics will provide a quick overview of Statistics Canada survey data.

    Release date: 2025-01-13
  • 2. Rural and Small Town Canada Analysis Bulletin
    Journals and periodicals: 21-006-X
    Geography: Canada
    Description: This series of analytical articles provides insights on the socio-economic environment in rural communities in Canada. New articles will be released periodically.
    Release date: 2025-01-13
  • 3. Insights on Canadian Society
    Journals and periodicals: 75-006-X
    Geography: Canada
    Description: This publication brings together and analyzes a wide range of data sources in order to provide information on various aspects of Canadian society, including labour, income, education, social, and demographic issues, that affect the lives of Canadians.
    Release date: 2025-01-13
  • 4. Analysis in Brief
    Journals and periodicals: 11-621-M
    Geography: Canada
    Description: The papers published in the Analysis in Brief analytical series shed light on current economic issues. Aimed at a general audience, they cover a wide range of topics including National Accounts, business enterprises, trade, transportation, agriculture, the environment, manufacturing, science and technology, services, etc.
    Release date: 2025-01-09
  • 5. Statistics Canada: Departmental Sustainable Development Strategy, 2023 to 2027
    Journals and periodicals: 45-26-0001
    Description: The Departmental Sustainable Development Strategy (DSDS) outlines departmental actions, with measurable performance indicators, that support the implementation strategies of the 2022-2026 Federal Sustainable Development Strategy. The DSDS further outlines Statistics Canada’s sustainable development vision to produce data to help track whether Canada is moving toward a more sustainable future and highlights projects with links to supporting sustainable development goals.
    Release date: 2024-12-27
  • 6. Analytical Studies: Methods and References
    Journals and periodicals: 11-633-X
    Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.
    Release date: 2024-12-20
  • 7. 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: 2024-12-20
  • 8. Economic and Social Reports
    Journals and periodicals: 36-28-0001
    Description: Economic and Social Reports includes in-depth research, brief analyses, and current economic updates on a variety of topics, such as labour, immigration, education and skills, income mobility, well-being, aging, firm dynamics, productivity, economic transitions, and economic geography. All the papers are institutionally reviewed and the research and analytical papers undergo peer review to ensure that they conform to Statistics Canada's mandate as a governmental statistical agency and adhere to generally accepted standards of good professional practice.
    Release date: 2024-12-19
  • 9. Health Reports
    Journals and periodicals: 82-003-X
    Geography: Canada
    Description:

    Health Reports, published by the Health Analysis Division of Statistics Canada, is a peer-reviewed journal of population health and health services research. It is designed for a broad audience that includes health professionals, researchers, policymakers, and the general public. The journal publishes articles of wide interest that contain original and timely analyses of national or provincial/territorial surveys or administrative databases. New articles are published electronically each month.

    Health Reports had an impact factor of 5.0 for 2022 and a five-year impact factor of 5.6. All articles are indexed in PubMed. Our online catalogue is free and receives more than 700,000 visits per year. External submissions are welcome.
    Release date: 2024-12-18
  • 10. Housing Statistics in Canada
    Journals and periodicals: 46-28-0001
    Description: This publication provides insights on housing data and analysis at Statistics Canada. Readers can access in-depth information on the latest housing data released by the Agency. The series relies on both descriptive and analytical methods to analyze administrative and survey data sets that relate to housing.
    Release date: 2024-12-16
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