Data analysis

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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) (20 to 30 of 26 results)

21. Life Cycle Bias in the Estimation of Intergenerational Earnings Persistence Archived
Surveys and statistical programs – Documentation: 11F0019M2003207
Geography: Canada
Description:
The estimation of intergenerational earnings mobility is rife with measurement problems since the research does not observe permanent, lifetime earnings. Nearly all studies make corrections for mean variation in earnings because of the age differences among respondents. Recent works employ average earnings or instrumental variable methods to address the effects of measurement error as a result of transitory earnings shocks and mis-reporting. However, empirical studies of intergenerational mobility have paid no attention to the changes in earnings variance across the life cycle suggested by economic models of human capital investment.
Using information from the Intergenerational Income Data from Canada and the National Longitudinal Survey and Panel Study of Income Dynamics from the United States, this study finds a strong association between age at observation and estimated earnings persistence. Part of this age-dependence is related to a general increase in transitory earnings variance during the collection of data. An independent effect of life cycle investment is also identified. These findings are then applied to the variation among intergenerational earnings persistence studies. Among studies with similar methodologies, one-third of the variance in published estimates of earnings persistence is attributable to cross-study differences in the age of responding fathers. Finally, these results call into question tests for the importance of credit constraints based on measures of earnings at different points in the life cycle.
Release date: 2003-08-05
22. Statistics Canada Total Work Accounts System: Technical Guide to the 1998 Edition Archived
Surveys and statistical programs – Documentation: 12-584-G
Description:
This book introduces technical aspects of the Statistics Canada Total Work Accounts System (TWAS). The TWAS is designed to facilitate the analysis of issues that require simultaneous consideration of both paid work and unpaid productive work. Its key contribution is to allocate the deemed output of each episode of unpaid work activity to a specific beneficiary or group of beneficiaries (called "destinations"). The guide presents the criteria used to decide the allocation of each work episode to one of the destinations, as well as the pseudo code for DESTIN, the key variable of the System. This pseudo code allows programmers to quickly create the actual programming code needed to derive the DESTIN variable in their own microdata files of diary-based time-use records. The guide also discusses illustrative applications of the System, as well as its key limitations.
Release date: 2002-02-12
23. National tourism indicators: A new tool for analysing tourism in Canada Archived
Notices and consultations: 87-003-X19970012882
Geography: Canada
Description:
The purpose of this article is to inform Travel-log readers of the availability of a new analytical tool - the National Tourism Indicators. These estimates, which measure trends in tourism in Canada, are placed in perspective here, taking into account the concepts and definitions used in developing them.
Release date: 1997-01-08
24. Alternative Measures of the Average Duration of Unemployment Archived
Surveys and statistical programs – Documentation: 11F0019M1995083
Geography: Canada
Description:
This paper examines the robustness of a measure of the average complete duration of unemployment in Canada to a host of assumptions used in its derivation. In contrast to the average incomplete duration of unemployment, which is a lagging cyclical indicator, this statistic is a coincident indicator of the business cycle. The impact of using a steady state as opposed to a non steady state assumption, as well as the impact of various corrections for response bias are explored. It is concluded that a non steady state estimator would be a valuable compliment to the statistics on unemployment duration that are currently released by many statistical agencies, and particularly Statistics Canada.
Release date: 1995-12-30
25. Labour Force Classification in the Survey of Labour and Income Dynamics (SLID): Evaluation of Test 3A Results Archived
Surveys and statistical programs – Documentation: 75F0002M1993014
Description:
This paper presents the results from test 3A of the Survey of Labour and Income Dynamics (SLID), conducted in January 1993, with a view to identify any necessary changes to the questions or to the algorithm used to derive labour force status.
Release date: 1995-12-30
26. SLID Derived Variables: Demographic, Cultural and Geographic Archived
Surveys and statistical programs – Documentation: 75F0002M1994018
Description:
This document describes the demographic, cultural and geographic derived variables for the Survey of Labour and Income Dynamics (SLID).
Release date: 1995-12-30

Date modified:: 2026-06-19

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