Statistical methods
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Results
All (2,478)
All (2,478) (0 to 10 of 2,478 results)
- Surveys and statistical programs – Documentation: 19-20-00012026001Description: This reference document provides nontechnical answers on selected topics related to the use and interpretation of seasonally adjusted data. It is designed to complement more technical discussions of seasonal adjustment found in Statistics Canada publications and reference manuals.Release date: 2026-05-11
- Surveys and statistical programs – Documentation: 19-20-0001Description: Documents in this series provide insight into the statistical methods used by Statistics Canada to produce official statistics. They include introductory material, in-depth descriptions of techniques and methods, best practices, and guidelines. All documents have undergone review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted methodological standards and practices.Release date: 2026-05-11
- Notices and consultations: 13-605-XDescription: This product contains articles related to the latest methodological, conceptual developments in the Canadian System of Macroeconomic Accounts as well as the analysis of the Canadian economy. It includes articles detailing new methods, concepts and statistical techniques used to compile the Canadian System of Macroeconomic Accounts. It also includes information related to new or expanded data products, provides updates and supplements to information found in various guides and analytical articles touching upon a broad range of topics related to the Canadian economy.Release date: 2026-05-04
- Surveys and statistical programs – Documentation: 11-633-X2026002Description: Recent changes in Canada’s immigration levels have heightened interest in understanding how immigration affects housing demand. This article develops a methodological framework for projecting housing use associated with permanent residents (PRs) and non-permanent residents (NPRs) under alternative immigration scenarios. The framework applies observed per capita housing use rates from the Census of Population to estimate incremental housing use by tenure over time.Release date: 2026-04-24
- 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: 2026-04-24
- 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
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2026-02-12
- Articles and reports: 13-604-M2026001Description: This documentation outlines the methodology used to develop the Distributions of household economic accounts published in January 2026 for the reference years 2010 to 2025. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.Release date: 2026-01-29
- Articles and reports: 12-001-X202500200001Description: Nested error regression models are commonly used to incorporate unit specific auxiliary variables to improve small area estimates. When the mean structure of the model is misspecified, the design-based mean squared prediction error (MSPE) of Empirical Best Linear Unbiased Predictors (EBLUP) generally increases. The Observed Best Prediction (OBP) method has been proposed with the intent to improve on the design-based MSPE over EBLUP. In this paper, we conduct a Monte Carlo simulation experiments to understand the effect of misspsecification of mean structures on different small area estimators. Our findings suggest that the OBP using unit-level auxiliary variables does not outperform the EBLUP in terms of design-based MSPE, unless the number of small areas m is extremely large. Conversely, the performance of OBP significantly improves when area-level auxiliary variables are employed. This paper includes both analytical and numerical evidence to demonstrate these observations, providing practical insights for addressing model misspecification in small area estimation (SAE).Release date: 2025-12-23
- Articles and reports: 12-001-X202500200002Description: This study examines interviewer effects on household nonresponse in three waves of the Household Finance and Consumption Survey (HFCS) in Austria using a multilevel model. Addressing nonresponse at its source is crucial for maintaining survey data quality and representativeness. Our findings indicate that the variation in response behavior explained by interviewer effects decreased from about one-third in the first wave to 7% in the third wave. Effective interviewers tend to have a university degree, be married, homeowners, and have a larger workload. Additionally, higher mean wages in the household’s municipality negatively affect survey participation. These insights suggest targeted interviewer selection and training strategies to improve response rates.Release date: 2025-12-23
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Data (10)
Data (10) ((10 results))
- Public use microdata: 89F0002XDescription: The SPSD/M is a static microsimulation model designed to analyse financial interactions between governments and individuals in Canada. It can compute taxes paid to and cash transfers received from government. It is comprised of a database, a series of tax/transfer algorithms and models, analytical software and user documentation.Release date: 2026-02-12
- Profile of a community or region: 46-26-0002Description: The National Address Register (NAR) is a list of commercial and residential addresses in Canada that are extracted from Statistics Canada's Building Register and deemed non-confidential.Release date: 2025-12-19
- Table: 89-26-0006Description: PASSAGES is an open-source dynamic microsimulation model aimed at supporting policy analysis and research relating to Canadian retirement income system outcomes at the individual and family level. The publicly available version includes a synthetic starting database, a model, and documentation. A confidential starting database is also available.Release date: 2025-03-12
- 4. 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
- Table: 11-10-0074-01Geography: Census tractFrequency: OccasionalDescription:
The divergence index (D-index) describes the degree that families with different income levels are mixing together in neighbourhoods. It compares neighbourhood (census tract, CT) discrete income distributions to a base distribution, which is the income quintiles of the neighbourhood’s census metropolitan area (CMA).
Release date: 2020-06-22 - 6. 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
- Table: 53-500-XDescription:
This report presents the results of a pilot survey conducted by Statistics Canada to measure the fuel consumption of on-road motor vehicles registered in Canada. This study was carried out in connection with the Canadian Vehicle Survey (CVS) which collects information on road activity such as distance traveled, number of passengers and trip purpose.
Release date: 2004-10-21 - Table: 13-220-XDescription: In the 1997 edition, new and revised benchmarks were introduced for 1992 and 1988. The indicators are used to monitor supply, demand and employment for tourism in Canada on a timely basis. The annual tables are derived using the National Income and Expenditure Accounts (NIEA) and various industry and travel surveys. Tables providing actual data and percentage changes, for seasonally adjusted current and constant price estimates are included. In addition, an analytical section provides graphs, and time series of first differences, percentage changes, and seasonal factors for selected indicators. Data are published from 1987 and the publication will be available on the day of release. New data are included in the demand tables for non-tourism commodities produced by non-tourism industries and in the employment tables covering direct tourism employment generated by non-tourism industries. This product was commissioned by the Canadian Tourism Commission to provide annual updates for the Tourism Satellite Account.Release date: 2003-01-08
- 9. Historical Statistics of Canada ArchivedTable: 11-516-XDescription:
The second edition of Historical statistics of Canada was jointly produced by the Social Science Federation of Canada and Statistics Canada in 1983. This volume contains about 1,088 statistical tables on the social, economic and institutional conditions of Canada from the start of Confederation in 1867 to the mid-1970s. The tables are arranged in sections with an introduction explaining the content of each section, the principal sources of data for each table, and general explanatory notes regarding the statistics. In most cases, there is sufficient description of the individual series to enable the reader to use them without consulting the numerous basic sources referenced in the publication.
The electronic version of this historical publication is accessible on the Internet site of Statistics Canada as a free downloadable document: text as HTML pages and all tables as individual spreadsheets in a comma delimited format (CSV) (which allows online viewing or downloading).
Release date: 1999-07-29 - 10. National Population Health Survey Overview ArchivedTable: 82-567-XDescription:
The National Population Health Survey (NPHS) is designed to enhance the understanding of the processes affecting health. The survey collects cross-sectional as well as longitudinal data. In 1994/95 the survey interviewed a panel of 17,276 individuals, then returned to interview them a second time in 1996/97. The response rate for these individuals was 96% in 1996/97. Data collection from the panel will continue for up to two decades. For cross-sectional purposes, data were collected for a total of 81,000 household residents in all provinces (except people on Indian reserves or on Canadian Forces bases) in 1996/97.
This overview illustrates the variety of information available by presenting data on perceived health, chronic conditions, injuries, repetitive strains, depression, smoking, alcohol consumption, physical activity, consultations with medical professionals, use of medications and use of alternative medicine.
Release date: 1998-07-29
Analysis (2,036)
Analysis (2,036) (30 to 40 of 2,036 results)
- Articles and reports: 11-522-X202500100008Description: In 2020, Statistics Canada started to use probabilistic web panels as an alternate method of collecting official statistics. In a web panel, respondents to another survey are asked for contact information to participate in future short surveys. This paper will highlight Statistics Canada's experience with panels after 4 years, including what has been learned about the recruitment of panel participants and how to subsequently collect data using panel surveys. The ways in which recruitment questions are presented can result in very different rates of participation. Moreover, the wealth of auxiliary information available on the recruitment survey can be used to actively manage panel collection operations, by predicting the probability of response and using this information to target follow-up efforts.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100009Description: Three series of web panels were implemented at Statistics Canada from 2020 to 2024. Participants for these web panel series were recruited from respondents of large probabilistic social surveys (recruitment surveys), and subsequently were invited to complete a series of short online surveys. Estimates of recruitment survey variables were calculated using both recruitment survey weights and web panel weights, and these were compared; differences signal the possibility of residual bias that was not corrected by the web panel weighting process. This investigation found more significant differences than would be expected if the web panel estimator fully corrected for the bias resulting from the web panel response process. Questions related to certain topics such as politics and voting, sense of belonging, and media consumption were found to have the most significant differences between web panel estimates and recruitment survey estimates.Release date: 2025-09-08
- 33. Life in the FastText Lane: Harnessing Linear Programming Constrained Machine Learning for Classifications Revision ArchivedArticles 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
- 34. Data-driven Imputation Strategies and their Associated Quality Indicators in Economic Surveys ArchivedArticles and reports: 11-522-X202500100011Description: The use of modern "data"-driven imputation methods to treat non-response in the context of surveys processed in the Integrated Business Statistics Program at Statistics Canada has previously been explored. It was observed that these methods can lead to high quality imputation and further have the potential to result in broad efficiencies when setting up a particular survey's edit and imputation strategy. However, estimation of the associated total variance, more specifically the component due to imputation, remains a challenge. In this article, two methods for estimation of total variance are proposed and show preliminary results that have motivated us to pursue further research in this area.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100012Description: In 2022, the Institut de la statistique du Québec conducted a survey of high school students in Nunavik, a unique, remote region of Quebec. The survey aimed to develop a portrait of the state of the students' physical and mental health, their lifestyle habits and their environment. This article describes the challenges encountered during the survey and the solutions put in place to overcome them.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100013Description: As part of answering the call to action for the United Nations' (UN) 17 Sustainable Development Goals, as well as addressing social, economic, and equity challenges within Canada, Statistics Canada's five-year development phase for the Disaggregated Data Action Plan (DDAP) was funded in 2021 to support data driven decision around these challenges. In turn, the document "Guiding Principles: Leveraging the 2021 Census of Populations Data for DDAP Groups of Interest" were created. The guiding principles document explains the organizational framework of the DDAP in the Agency, describes existing data sources, addresses ethical and privacy concerns, and centralizes sampling methods tailored for DDAP initiatives while accounting for characteristics which can complicate sampling and data collection procedures.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100014Description: Artificial intelligence (AI) with its subfield machine learning (ML) has found its way into administration in general and also into official statistics in Germany in particular. This paper highlights the ethical issues that may arise when using AI/ML in official statistics and examines whether a separate ethical framework is needed to deal with these issues appropriately, as is proposed by institutions of other countries and intergovernmental institutions related to official statistics. The results of the study are presented to show that the implementation of the requirements of the existing and mostly non-AI/ML-specific frames of reference such as law and quality is already sufficient to adequately address the ethical issues based on risk scenarios.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100015Description: Currently, Statistics Canada has no official guidance on confidentiality rules for releasing small area estimate. In recent years, there has been increasing demand from Research Data Centre (RDC) researchers for comprehensive confidentiality guidelines such that they can publish small area estimates in their research. This confidentiality analysis applies to area-level small area estimation.Release date: 2025-09-08
- Articles and reports: 11-522-X202500100016Description: The adoption of synthetic data generation as a confidentiality measure is increasing in statistical agencies worldwide, including at Statistics Canada. This approach provides an alternative to the traditional dissemination of anonymized public microdata files, offering both privacy protection and data utility. However, the creation of synthetic data presents challenges in assessing and mitigating disclosure risks. This paper reviews the different types of disclosure risks, that being attribute, membership and identity disclosure, and presents some of the associated methods for measuring risk. The paper presents prominent risk assessment metrics and discusses practical methods for disclosure control in data synthesis. Methods for assessing disclosure risks usually produce a metric that can be used to gauge the risk, but there is little consensus on threshold values for these metrics. It is also important to focus on importance of balancing utility and confidentiality, which needs further discussion in context of these methods. The paper concludes by offering insights and recommendations about managing disclosure risk while creating synthetic data as well as providing some ideas on future directions for research and practical implications for managing disclosure risks in synthetic data.Release date: 2025-09-08
- 40. Exploration of Deep Learning Synthetic Data Generation for Sensitive Utility Data Sharing ArchivedArticles and reports: 11-522-X202500100017Description: Utilities hold crucial information about energy usage and building characteristics which can be utilized by government agencies to improve their corresponding analytics. However, this data is associated with private customer records and thus the building data and energy usage may be too sensitive to share. Often, high-level aggregated versions of this data are shared through robust contracts, limiting the statistics that can be derived. With the advancement of generative machine learning techniques, Statistics Canada and Natural Resources Canada have explored the feasibility of using these models to produce synthetic versions of utility data which may be shared in full to requesting organizations. These synthetic datasets can be created by a utility company through a locally run program and the outputs can be approved before being sent. This work has identified that certain generative models can feasibly be used by utilities to generate new versions of a dataset and has identified the issues which must be addressed prior to implementing this in practice. Both tabular and time-series models have been tested for different data sharing scenarios, where the TimeGAN model successfully captured the general energy peaks and valleys over a given day with reasonable computational requirements. Although this process takes days for annual energy amounts over thousands of customer records, this can enable new data sharing initiatives between utilities and National Statistical Offices while managing privacy risks. As work progresses in future phases with real utility partners, trust can be built for these approaches, and they can begin being tested on real data by actual data holders.Release date: 2025-09-08
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Reference (380)
Reference (380) (50 to 60 of 380 results)
- 51. Using family-related variables from the Census of Population and the National Household Survey microdata files ArchivedSurveys and statistical programs – Documentation: 91F0015M2016012Description:
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 - Notices and consultations: 92-140-X2016001Description:
The 2016 Census Program Content Test was conducted from May 2 to June 30, 2014. The Test was designed to assess the impact of any proposed content changes to the 2016 Census Program and to measure the impact of including a social insurance number (SIN) question on the data quality.
This quantitative test used a split-panel design involving 55,000 dwellings, divided into 11 panels of 5,000 dwellings each: five panels were dedicated to the Content Test while the remaining six panels were for the SIN Test. Two models of test questionnaires were developed to meet the objectives, namely a model with all the proposed changes EXCEPT the SIN question and a model with all the proposed changes INCLUDING the SIN question. A third model of 'control' questionnaire with the 2011 content was also developed. The population living in a private dwelling in mail-out areas in one of the ten provinces was targeted for the test. Paper and electronic response channels were part of the Test as well.
This report presents the Test objectives, the design and a summary of the analysis in order to determine potential content for the 2016 Census Program. Results from the data analysis of the Test were not the only elements used to determine the content for 2016. Other elements were also considered, such as response burden, comparison over time and users’ needs.
Release date: 2016-04-01 - Surveys and statistical programs – Documentation: 11-522-X201700014706Description:
Over the last decade, Statistics Canada’s Producer Prices Division has expanded its service producer price indexes program and continued to improve its goods and construction producer price indexes program. While the majority of price indexes are based on traditional survey methods, efforts were made to increase the use of administrative data and alternative data sources in order to reduce burden on our respondents. This paper focuses mainly on producer price programs, but also provides information on the growing importance of alternative data sources at Statistics Canada. In addition, it presents the operational challenges and risks that statistical offices could face when relying more and more on third-party outputs. Finally, it presents the tools being developed to integrate alternative data while collecting metadata.
Release date: 2016-03-24 - 54. Challenges and results in using Audit trail data to monitor Labour Force Survey data quality ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014707Description:
The Labour Force Survey (LFS) is a monthly household survey of about 56,000 households that provides information on the Canadian labour market. Audit Trail is a Blaise programming option, for surveys like LFS with Computer Assisted Interviewing (CAI), which creates files containing every keystroke and edit and timestamp of every data collection attempt on all households. Combining such a large survey with such a complete source of paradata opens the door to in-depth data quality analysis but also quickly leads to Big Data challenges. How can meaningful information be extracted from this large set of keystrokes and timestamps? How can it help assess the quality of LFS data collection? The presentation will describe some of the challenges that were encountered, solutions that were used to address them, and results of the analysis on data quality.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 11-522-X201700014708Description:
Statistics Canada’s Household Survey Frames (HSF) Programme provides various universe files that can be used alone or in combination to improve survey design, sampling, collection, and processing in the traditional “need to contact a household model.” Even as surveys are migrating onto these core suite of products, the HSF is starting to plan the changes to infrastructure, organisation, and linkages with other data assets in Statistics Canada that will help enable a shift to increased use of a wide variety of administrative data as input to the social statistics programme. The presentation will provide an overview of the HSF Programme, foundational concepts that will need to be implemented to expand linkage potential, and will identify strategic research being under-taken toward 2021.
Release date: 2016-03-24 - 56. The Data Warehouse and analytical tools to facilitate the integration of the Canadian Macroeconomic Accounts ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014710Description:
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 - Surveys and statistical programs – Documentation: 11-522-X201700014716Description:
Administrative data, depending on its source and original purpose, can be considered a more reliable source of information than survey-collected data. It does not require a respondent to be present and understand question wording, and it is not limited by the respondent’s ability to recall events retrospectively. This paper compares selected survey data, such as demographic variables, from the Longitudinal and International Study of Adults (LISA) to various administrative sources for which LISA has linkage agreements in place. The agreement between data sources, and some factors that might affect it, are analyzed for various aspects of the survey.
Release date: 2016-03-24 - 58. Student Pathways and Graduate Outcomes ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014717Description:
Files with linked data from the Statistics Canada, Postsecondary Student Information System (PSIS) and tax data can be used to examine the trajectories of students who pursue postsecondary education (PSE) programs and their post-schooling labour market outcomes. On one hand, administrative data on students linked longitudinally can provide aggregate information on student pathways during postsecondary studies such as persistence rates, graduation rates, mobility, etc. On the other hand, the tax data could supplement the PSIS data to provide information on employment outcomes such as average and median earnings or earnings progress by employment sector (industry), field of study, education level and/or other demographic information, year over year after graduation. Two longitudinal pilot studies have been done using administrative data on postsecondary students of Maritimes institutions which have been longitudinally linked and linked to Statistics Canada Ttx data (the T1 Family File) for relevant years. This article first focuses on the quality of information in the administrative data and the methodology used to conduct these longitudinal studies and derive indicators. Second, it will focus on some limitations when using administrative data, rather than a survey, to define some concepts.
Release date: 2016-03-24 - 59. Using data linkage to evaluate the consistency of place of residence between census data and tax data ArchivedSurveys and statistical programs – Documentation: 11-522-X201700014725Description:
Tax data are being used more and more to measure and analyze the population and its characteristics. One of the issues raised by the growing use of these type of data relates to the definition of the concept of place of residence. While the census uses the traditional concept of place of residence, tax data provide information based on the mailing address of tax filers. Using record linkage between the census, the National Household Survey and tax data from the T1 Family File, this study examines the consistency level of the place of residence of these two sources and its associated characteristics.
Release date: 2016-03-24 - Surveys and statistical programs – Documentation: 11-522-X201700014726Description:
Internal migration is one of the components of population growth estimated at Statistics Canada. It is estimated by comparing individuals’ addresses at the beginning and end of a given period. The Canada Child Tax Benefit and T1 Family File are the primary data sources used. Address quality and coverage of more mobile subpopulations are crucial to producing high-quality estimates. The purpose of this article is to present the results of evaluations of these elements using access to more tax data sources at Statistics Canada.
Release date: 2016-03-24
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