Data analysis

Results

All (289)

All (289) (0 to 10 of 289 results)

1. Quantitative impact analysis: A practical overview
Articles and reports: 36-28-0001202600500003
Description: This spotlight article outlines practical methods for assessing the economic impacts of public programs delivered by federal agencies and Crown corporations. It summarizes key steps in conducting quantitative impact analysis, including data linkage, cohort construction and implementation of quasi causal estimators.
Release date: 2026-05-27
2. 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: 2026-05-27
3. When and How to Use Area-Level Measures for Health Analysis: A Review and Recommendation Report
Surveys and statistical programs – Documentation: 11-633-X2026001
Description: This report defines key concepts related to area-level analysis and introduces area-level measures developed and utilized at Statistics Canada for health analysis. It also provides a decision-making framework and practical recommendations to help researchers select appropriate methods. The goal is to guide readers on when area-level analysis is appropriate and what type of area-level measure is suitable to achieve research objectives.
Release date: 2026-03-05
4. Collinearity diagnostics in generalized linear models fitted with survey data
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
5. 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
6. Life in the FastText Lane: Harnessing Linear Programming Constrained Machine Learning for Classifications Revision Archived
Articles and reports: 11-522-X202500100010
Description: Statistics Canada's Labour Force Survey (LFS) plays an essential role in the estimation of labour market conditions in Canada. Periodically, LFS revises its data to the most recent industry and occupational classification versions. Differences in versions can be extensive, including high-level and unit-group structural changes, creations, deletions, split-offs and combination of classification units (classes). Historically, to reconcile split-off classes - where one class splits into multiple classes - a sample of LFS split-off records would be manually recoded to the new classification version. Based on the split-off proportion observed in the recoded sample, a random allocation method would be applied on all data to reflect the changing Canadian labour market over time. This article proposes using machine learning (fastText), constrained to split-off proportions using linear programming, to revise industry and occupation classifications in LFS. The hybrid framework benefits from a text-based revision mechanism while adhering to traditional proportions driven estimates, thus ensuring a minimal impact on the comparability of published labour market indicators.
Release date: 2025-09-08
7. Leveraging Statistics Canada data integration opportunities for program evaluation
Articles and reports: 36-28-0001202500300002
Description: Government programs are evaluated to measure their effectiveness. This article discusses the benefits of using Statistics Canada data combined with the data collected from the government program to provide a far more comprehensive evaluation than program data alone can offer. The article also summarizes a recent example of a program evaluation that benefited from Statistics Canada data and the expertise of Statistics Canada researchers in analyzing the data.
Release date: 2025-03-26
8. 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
9. 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
10. Longitudinal Immigration Database (IMDB) Technical Report, 2023
Surveys and statistical programs – Documentation: 11-633-X2024004
Description: 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: 2024-12-09

Data (2)

Data (2) ((2 results))

1. 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
2. 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

Analysis (256)

Analysis (256) (0 to 10 of 256 results)

1. Quantitative impact analysis: A practical overview
Articles and reports: 36-28-0001202600500003
Description: This spotlight article outlines practical methods for assessing the economic impacts of public programs delivered by federal agencies and Crown corporations. It summarizes key steps in conducting quantitative impact analysis, including data linkage, cohort construction and implementation of quasi causal estimators.
Release date: 2026-05-27
2. 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: 2026-05-27
3. Collinearity diagnostics in generalized linear models fitted with survey data
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
4. 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
5. Life in the FastText Lane: Harnessing Linear Programming Constrained Machine Learning for Classifications Revision Archived
Articles and reports: 11-522-X202500100010
Description: Statistics Canada's Labour Force Survey (LFS) plays an essential role in the estimation of labour market conditions in Canada. Periodically, LFS revises its data to the most recent industry and occupational classification versions. Differences in versions can be extensive, including high-level and unit-group structural changes, creations, deletions, split-offs and combination of classification units (classes). Historically, to reconcile split-off classes - where one class splits into multiple classes - a sample of LFS split-off records would be manually recoded to the new classification version. Based on the split-off proportion observed in the recoded sample, a random allocation method would be applied on all data to reflect the changing Canadian labour market over time. This article proposes using machine learning (fastText), constrained to split-off proportions using linear programming, to revise industry and occupation classifications in LFS. The hybrid framework benefits from a text-based revision mechanism while adhering to traditional proportions driven estimates, thus ensuring a minimal impact on the comparability of published labour market indicators.
Release date: 2025-09-08
6. Leveraging Statistics Canada data integration opportunities for program evaluation
Articles and reports: 36-28-0001202500300002
Description: Government programs are evaluated to measure their effectiveness. This article discusses the benefits of using Statistics Canada data combined with the data collected from the government program to provide a far more comprehensive evaluation than program data alone can offer. The article also summarizes a recent example of a program evaluation that benefited from Statistics Canada data and the expertise of Statistics Canada researchers in analyzing the data.
Release date: 2025-03-26
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. Unlock the Power of Data Linkage
Stats in brief: 89-20-00062024003
Description: This video is intended for professionals, policymakers, and researchers who are interested in understanding how data linkage can be used to gain deeper insights into various issues. It demonstrates how combining data from different sources can help address gaps in information, leading to better-informed policies and improved outcomes.
Release date: 2024-11-25
10. Labour Force Survey initiatives under Statistics Canada’s Disaggregated Data Action Plan Archived
Articles and reports: 11-522-X202200100004
Description: In accordance with Statistics Canada’s long-term Disaggregated Data Action Plan (DDAP), several initiatives have been implemented into the Labour Force Survey (LFS). One of the more direct initiatives was a targeted increase in the size of the monthly LFS sample. Furthermore, a regular Supplement program was introduced, where an additional series of questions are asked to a subset of LFS respondents and analyzed in a monthly or quarterly production cycle. Finally, the production of modelled estimates based on Small Area Estimation (SAE) methodologies resumed for the LFS and will include a wider scope with more analytical value than what had existed in the past. This paper will give an overview of these three initiatives.
Release date: 2024-03-25

Reference (26)

Reference (26) (0 to 10 of 26 results)

1. When and How to Use Area-Level Measures for Health Analysis: A Review and Recommendation Report
Surveys and statistical programs – Documentation: 11-633-X2026001
Description: This report defines key concepts related to area-level analysis and introduces area-level measures developed and utilized at Statistics Canada for health analysis. It also provides a decision-making framework and practical recommendations to help researchers select appropriate methods. The goal is to guide readers on when area-level analysis is appropriate and what type of area-level measure is suitable to achieve research objectives.
Release date: 2026-03-05
2. Longitudinal Immigration Database (IMDB) Technical Report, 2023
Surveys and statistical programs – Documentation: 11-633-X2024004
Description: 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: 2024-12-09
3. Longitudinal Immigration Database (IMDB) Technical Report, 2022
Surveys and statistical programs – Documentation: 11-633-X2024001
Description: 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 35 years.
Release date: 2024-01-22
4. Agriculture–Population Linkage: Data quality report
Surveys and statistical programs – Documentation: 32-26-0006
Description: This report provides data quality information pertaining to the Agriculture–Population Linkage, such as sources of error, matching process, response rates, imputation rates, sampling, weighting, disclosure control methods and data quality indicators.
Release date: 2023-08-25
5. Aggregated and derived income concepts and income statistics, 2021 Census of Population
Surveys and statistical programs – Documentation: 98-20-00032021011
Description: This video explains the key concepts of different levels of aggregation of income data such as household and family income; income concepts derived from key income variables such as adjusted income and equivalence scale; and statistics used for income data such as median and average income, quartiles, quintiles, deciles and percentiles.
Release date: 2023-03-29
6. Low-income concepts and statistics, 2021 Census of Population
Surveys and statistical programs – Documentation: 98-20-00032021012
Description: This video builds on concepts introduced in the other videos on income. It explains key low-income concepts - Market Basket Measure (MBM), Low income measure (LIM) and Low-income cut-offs (LICO) and the indicators associated with these concepts such as the low-income gap and the low-income ratio. These concepts are used in analysis of the economic well-being of the population.
Release date: 2023-03-29
7. Longitudinal Immigration Database (IMDB) Technical Report, 2021
Surveys and statistical programs – Documentation: 11-633-X2022009
Description: 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 35 years.

This report will discuss the IMDB data sources, concepts and variables, record linkage, data processing, dissemination, data evaluation and quality indicators, comparability with other immigration datasets, and the analyses possible with the IMDB.
Release date: 2022-12-05
8. Painting a Portrait of Canada: The 2021 Census of Population
Notices and consultations: 98-26-0001
Description:
This white paper presents Statistics Canada’s planned approach to the 2021 Census of Population and provides a clear explanation of the processes behind the census program, touching on historical, legal, operational and content aspects. Statistics Canada recognizes that it is important to not only successfully conduct the census, but also to be transparent and informative about the way in which those efforts are accomplished. Painting a Portrait of Canada: The 2021 Census of Population gives readers an exclusive, detailed look at how census data is collected, analyzed and given back to Canadians, in the form of high-quality statistical information, used to make evidence-based decisions in Canadian society.
Release date: 2020-07-20
9. Using family-related variables from the Census of Population and the National Household Survey microdata files Archived
Surveys and statistical programs – Documentation: 91F0015M2016012
Description:
This article provides information on using family-related variables from the microdata files of Canada’s Census of Population. These files exist internally at Statistics Canada, in the Research Data Centres (RDCs), and as public-use microdata files (PUMFs). This article explains certain technical aspects of all three versions, including the creation of multi-level variables for analytical purposes.
Release date: 2016-12-22
10. The Data Warehouse and analytical tools to facilitate the integration of the Canadian Macroeconomic Accounts Archived
Surveys and statistical programs – Documentation: 11-522-X201700014710
Description:
The Data Warehouse has modernized the way the Canadian System of Macroeconomic Accounts (MEA) are produced and analyzed today. Its continuing evolution facilitates the amounts and types of analytical work that is done within the MEA. It brings in the needed element of harmonization and confrontation as the macroeconomic accounts move toward full integration. The improvements in quality, transparency, and timeliness have strengthened the statistics that are being disseminated.
Release date: 2016-03-24

Date modified:: 2026-06-18

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