Data analysis
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Survey or statistical program
- Census of Population (13)
- Canadian Community Health Survey - Annual Component (7)
- Labour Force Survey (7)
- Survey of Household Spending (6)
- Canadian Income Survey (4)
- Survey of Labour and Income Dynamics (3)
- Longitudinal Immigration Database (3)
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- Monthly Oil and Other Liquid Petroleum Products Pipeline Survey (2)
- Uniform Crime Reporting Survey (2)
- Census of Agriculture (2)
- Households and the Environment Survey (2)
- Time Use Survey (2)
- Biennial Drinking Water Plants Survey (2)
- Longitudinal Employment Analysis Program (2)
- Canada's International Transactions in Services (1)
- Waste Management Industry Survey: Government Sector (1)
- National Balance Sheet Accounts (1)
- National Gross Domestic Product by Income and by Expenditure Accounts (1)
- National Tourism Indicators (1)
- Biennial Waste Management Survey (1)
- Monthly Electricity Supply and Disposition Survey (1)
- Annual Electricity Supply and Disposition Survey (1)
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- Survey of Employment, Payrolls and Hours (1)
- Survey of Financial Security (1)
- Monthly Passenger Bus and Urban Transit Survey (1)
- Stock and Consumption of Fixed Non-residential Capital (1)
- Tuition and Living Accommodation Costs (1)
- Vital Statistics - Death Database (1)
- Annual Demographic Estimates: Canada, Provinces and Territories (1)
- Homeowner Repair and Renovation Survey (1)
- Annual Income Estimates for Census Families and Individuals (T1 Family File) (1)
- Annual Survey of Research and Development in Canadian Industry (1)
- Research and Development of Canadian Private Non-Profit Organizations (1)
- General Social Survey - Victimization (1)
- Postsecondary Student Information System (1)
- General Social Survey - Social Identity (1)
- Culture Services Trade (1)
- Canadian Community Health Survey - Nutrition (1)
- Canadian System of Environmental-Economic Accounts - Physical Flow Accounts (1)
- Air Quality Indicators (1)
- Freshwater Quality Indicator (1)
- Longitudinal and International Study of Adults (1)
- Government Finance Statistics (1)
- National Household Survey (1)
- Gross Domestic Expenditures on Research and Development (1)
- Survey of Safety in Public and Private Spaces (1)
- Canadian Housing Statistics Program (1)
- Study on International Money Transfers (1)
- Canadian Housing Survey (1)
- Survey on Early Learning and Child Care Arrangements (SELCCA) (1)
- Canadian Perspectives Survey Series (CPSS) (1)
- Canada Mortgage and Housing Corporation (1)
Results
All (289)
All (289) (0 to 10 of 289 results)
- Articles and reports: 36-28-0001202600500003Description: 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
- Journals and periodicals: 11-633-XDescription: 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
- Surveys and statistical programs – Documentation: 11-633-X2026001Description: 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
- Articles and reports: 12-001-X202500200004Description: 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
- Stats in brief: 89-20-00062025001Description: 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
- Articles and reports: 11-522-X202500100010Description: 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
- Articles and reports: 36-28-0001202500300002Description: 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
- Articles and reports: 12-001-X202400200004Description: 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
- Articles and reports: 12-001-X202400200005Description: 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
- Surveys and statistical programs – Documentation: 11-633-X2024004Description: 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
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Data (2)
Data (2) ((2 results))
- 1. Canadian Statistical Geospatial Explorer Hub ArchivedData Visualization: 71-607-X2020010Description: 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 ArchivedData Visualization: 71-607-X2019010Description: 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) (30 to 40 of 256 results)
- Stats in brief: 89-20-00082021001Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-29
- Stats in brief: 89-20-00082021002Description: This video is part of the confidentiality vetting support series and presents examples of how to use SAS to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021003Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- 34. Confidentiality Vetting Support: Dominance and homogeneity using the tcensus function (Stata) ArchivedStats in brief: 89-20-00082021004Description: This video is part of the confidentiality vetting support series and presents examples of how to use Stata to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Stats in brief: 89-20-00082021005Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to create proportion output for researchers working with confidential data.Release date: 2022-04-27
- Stats in brief: 89-20-00082021006Description: This video is part of the confidentiality vetting support series and presents examples of how to use R to perform the dominance and homogeneity test while using the Census.Release date: 2022-04-27
- Stats in brief: 11-627-M2022016Description:
This infographic explains the steps involved in collecting data for all Statistics Canada household and business surveys. The responses are compiled, analyzed and used to make important decisions and are kept strictly confidential.
Release date: 2022-02-28 - Articles and reports: 11-522-X202100100029Description:
In line with the path taken by the European Statistical System, Istat is investing on innovative methods to harness Big Data sources and to use them for the production of new and enriched Official Statistics products. Big Data sources are not, in general, directly tractable with traditional statistical techniques, just think of specific data types such as images and texts that are examples of the Variety dimension of Big Data. This motivates and justifies the growing interest of National Statistical Institutes in data science techniques. Istat is currently using data science techniques, including machine learning techniques, in innovation projects and for the publication of experimental statistics. This paper will provide an overview of the main current projects by Istat and will focus on two specific Big Data-based production pipelines, related to the processing of respectively text sources and imagery sources. The paper will highlight the main challenges these two pipelines and the solutions put in place to solve them.
Key Words: Machine Learning; Text Processing; Image Processing; Big Data
Release date: 2021-11-05 - Articles and reports: 11-522-X202100100008Description:
Non-probability samples are being increasingly explored by National Statistical Offices as a complement to probability samples. We consider the scenario where the variable of interest and auxiliary variables are observed in both a probability and non-probability sample. Our objective is to use data from the non-probability sample to improve the efficiency of survey-weighted estimates obtained from the probability sample. Recently, Sakshaug, Wisniowski, Ruiz and Blom (2019) and Wisniowski, Sakshaug, Ruiz and Blom (2020) proposed a Bayesian approach to integrating data from both samples for the estimation of model parameters. In their approach, non-probability sample data are used to determine the prior distribution of model parameters, and the posterior distribution is obtained under the assumption that the probability sampling design is ignorable (or not informative). We extend this Bayesian approach to the prediction of finite population parameters under non-ignorable (or informative) sampling by conditioning on appropriate survey-weighted statistics. We illustrate the properties of our predictor through a simulation study.
Key Words: Bayesian prediction; Gibbs sampling; Non-ignorable sampling; Statistical data integration.
Release date: 2021-10-29 - Articles and reports: 11-522-X202100100009Description:
Use of auxiliary data to improve the efficiency of estimators of totals and means through model-assisted survey regression estimation has received considerable attention in recent years. Generalized regression (GREG) estimators, based on a working linear regression model, are currently used in establishment surveys at Statistics Canada and several other statistical agencies. GREG estimators use common survey weights for all study variables and calibrate to known population totals of auxiliary variables. Increasingly, many auxiliary variables are available, some of which may be extraneous. This leads to unstable GREG weights when all the available auxiliary variables, including interactions among categorical variables, are used in the working linear regression model. On the other hand, new machine learning methods, such as regression trees and lasso, automatically select significant auxiliary variables and lead to stable nonnegative weights and possible efficiency gains over GREG. In this paper, a simulation study, based on a real business survey sample data set treated as the target population, is conducted to study the relative performance of GREG, regression trees and lasso in terms of efficiency of the estimators.
Key Words: Model assisted inference; calibration estimation; model selection; generalized regression estimator.
Release date: 2021-10-29
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Reference (26)
Reference (26) (10 to 20 of 26 results)
- Notices and consultations: 75-513-X2014001Description:
Starting with the 2012 reference year, annual individual and family income data is produced by the Canadian Income Survey (CIS). The CIS is a cross-sectional survey developed to provide information on the income and income sources of Canadians, along with their individual and household characteristics. The CIS reports on many of the same statistics as the Survey of Labour and Income Dynamics (SLID), which last reported on income for the 2011 reference year. This note describes the CIS methodology, as well as the main differences in survey objectives, methodology and questionnaires between CIS and SLID.
Release date: 2014-12-10 - 12. Using a Trend-cycle Approach to Estimate Changes in Southern Canada's Water Yield from 1971 to 2004 ArchivedSurveys and statistical programs – Documentation: 16-001-M2010014Description: Quantifying how Canada's water yield has changed over time is an important component of the water accounts maintained by Statistics Canada. This study evaluates the movement in the series of annual water yield estimates for Southern Canada from 1971 to 2004. We estimated the movement in the series using a trend-cycle approach and found that water yield for southern Canada has generally decreased over the period of observation.Release date: 2010-09-13
- 13. Finding and Using Statistics ArchivedSurveys and statistical programs – Documentation: 11-533-XDescription:
This guide has been created especially for users needing a step-by-step review on how to find, read and use data, with quick tips on locating information on the Statistics Canada website. Originally published in paper format in the 1980s, revised as part of the 1994 Statistics Canada Catalogue, and then transformed into an electronic version, this guide is continually being updated to maintain its currency and usefulness.
Release date: 2007-11-19 - Surveys and statistical programs – Documentation: 81-595-M2007056Geography: CanadaDescription: This handbook discusses the collection and interpretation of statistical data on Canada's trade in culture services.Release date: 2007-10-31
- 15. Producing Hours Worked for the SNA in Order to Measure Productivity: The Canadian Experience ArchivedSurveys and statistical programs – Documentation: 15-206-X2006004Description:
This paper provides a brief description of the methodology currently used to produce the annual volume of hours worked consistent with the System of National Accounts (SNA). These data are used for labour input in the annual and quarterly measures of labour productivity, as well as in the annual measures of multifactor productivity. For this purpose, hours worked are broken down by educational level and age group, so that changes in the composition of the labour force can be taken into account. They are also used to calculate hourly compensation and the unit labour cost and for simulations of the SNA Input-Output Model; as such, they are integrated as labour force inputs into most SNA satellite accounts (i.e., environment, tourism).
Release date: 2006-10-27 - Surveys and statistical programs – Documentation: 62F0026M2005005Description:
This discussion paper reviews the previous research into the subject of presenting historical time series and comparisons in constant dollars for the Survey of Household Spending (SHS), and its predecessor the Family Expenditure Survey (FAMEX). It examines two principal methods of converting spending data into constant dollars. The purpose of this discussion paper is to show interested parties how the two methods differ in complexity of implementation and interpretation.
Release date: 2005-07-15 - 17. The CRISP-NLSCY files ArchivedNotices and consultations: 12-002-X20050018033Description:
Dr. J. Douglas Willms, and his staff at the Canadian Research Institute for Social Policy (CRISP) at the University of New Brunswick (Fredericton Campus), have developed a set of files for researchers interested in using Statistics Canada's National Longitudinal Survey of Children and Youth (NLSCY) data sets. "The Files" consist of SPSS data and syntax, which are intended to assist researchers in conducting more efficient longitudinal analyses, using NLSCY data.
Release date: 2005-06-23 - Surveys and statistical programs – Documentation: 62F0026M2005001Description:
This paper provides some guidance to users on the use of medians and also gives some examples of situations when it can be a more appropriate measure than the average.
Release date: 2005-05-17 - Surveys and statistical programs – Documentation: 81-595-M2004020Geography: CanadaDescription:
This article discusses the collection and interpretation of statistical data on Canada's trade in culture goods. It defines the products that are included in culture trade and explains how appropriate products are selected from the relevant classification standards.
This version has been replaced by Culture Goods Trade Data User Guide, Catalogue No. 81-595-MIE2006040.
Release date: 2004-07-28 - Surveys and statistical programs – Documentation: 92-388-XDescription:
This report contains basic conceptual and data quality information to help users interpret and make use of census occupation data. It gives an overview of the collection, coding (to the 2001 National Occupational Classification), edit and imputation of the occupation data from the 2001 Census. The report describes procedural changes between the 2001 and earlier censuses, and provides an analysis of the quality level of the 2001 Census occupation data. Finally, it details the revision of the 1991 Standard Occupational Classification used in the 1991 and 1996 Censuses to the 2001 National Occupational Classification for Statistics used in 2001. The historical comparability of data coded to the two classifications is discussed. Appendices to the report include a table showing historical data for the 1991, 1996 and 2001 Censuses.
Release date: 2004-07-15