Keyword search
Filter results by
Search HelpKeyword(s)
Subject
- Agriculture and food (2)
- Business and consumer services and culture (1)
- Business performance and ownership (2)
- Children and youth (5)
- Digital economy and society (2)
- Economic accounts (12)
- Education, training and learning (2)
- Families, households and marital status (2)
- Government (1)
- Health (17)
- Housing (3)
- Immigration and ethnocultural diversity (10)
- Income, pensions, spending and wealth (9)
- International trade (1)
- Labour (3)
- Languages (1)
- Population and demography (7)
- Prices and price indexes (2)
- Retail and wholesale (1)
- Science and technology (1)
- Society and community (6)
- Statistical methods (145)
- Transportation (1)
Type
Year of publication
Survey or statistical program
- Census of Population (5)
- Longitudinal Immigration Database (4)
- National Household Survey (4)
- Survey of Household Spending (2)
- Survey of Labour and Income Dynamics (2)
- Canadian Health Measures Survey (2)
- Gross Domestic Product by Industry - National (Monthly) (1)
- Supply, Use and Input-Output Tables (1)
- National Gross Domestic Product by Income and by Expenditure Accounts (1)
- Consumer Price Index (1)
- Canadian Community Health Survey - Annual Component (1)
- Census of Agriculture (1)
- Programme for the International Assessment of Adult Competencies (1)
- National Longitudinal Survey of Children and Youth (1)
- General Social Survey - Social Identity (1)
- Labour Productivity Measures - Provinces and Territories (Annual) (1)
- Aboriginal Children's Survey (1)
- Longitudinal and International Study of Adults (1)
- Canadian Income Survey (1)
- Canadian Housing Statistics Program (1)
- Canadian Housing Survey (1)
- Labour Market Indicators (1)
Results
All (180)
All (180) (30 to 40 of 180 results)
- Articles and reports: 75F0002M2022001Description:
Periodically, income statistics are updated to reflect the most recent population estimates derived after the census. Accordingly, with the release of the 2020 data from the Canadian Income Survey (CIS), Statistics Canada has revised estimates for 2012 to 2019 using totals from population estimates based on the 2016 Census. This paper presents a comparison between revised and unrevised estimates for key income series, and describes other modifications made to CIS variables.
Release date: 2022-03-23 - Articles and reports: 46-28-0001202200100001Description:
When a survey publishes statistics with a quality indicator, it is usually derived from measures based on sampling theory. The production of quality indicators is a significant challenge when statistics are produced using alternative sources for which no sampling is done. This paper describes a new method used to create a quality indicator that combines indicators obtained at different stages of data processing. An example of the application of the method in the Canadian Housing Statistics Program is provided in the Appendix.
Release date: 2022-01-06 - Surveys and statistical programs – Documentation: 11-633-X2021008Description: 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. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. 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: 2021-12-06
- 34. Statistics 101: Proportions, ratios, and rates ArchivedStats in brief: 89-20-00062021003Description:
In this video, viewers will learn the differences between three types of measure: proportions, ratios, and rates. In addition, viewers by the end of this video will be able to determine how each measure is calculated and when it is best to use one measure rather than the other.
Release date: 2021-05-03 - 35. Measuring proximity to services and amenities: An experimental set of indicators for neighbourhoods and localities ArchivedArticles and reports: 18-001-X2020001Description:
This paper presents the methodology used to generate the first nationwide database of proximity measures and the results obtained with a first set of ten measures. The computational methods are presented as a generalizable model due to the fact that it is now possible to apply similar methods to a multitude of other services or amenities, in a variety of alternative specifications.
Release date: 2021-02-15 - Surveys and statistical programs – Documentation: 11-633-X2021002Description:
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. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. 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: 2021-02-01 - Articles and reports: 62F0026M2020001Description:
Since the 2010 Survey of Household Spending redesign, statistics on the annual proportion of households reporting expenditures and the annual average expenditure per reporting household have not been available for many good and service categories. To help fill this data gap for users, a statistical model was developed in order to produce approximations of these statistics. This product consists of data tables and a user guide.
Release date: 2021-01-07 - Articles and reports: 12-001-X202000200003Description:
We combine weighting and Bayesian prediction in a unified approach to survey inference. The general principles of Bayesian analysis imply that models for survey outcomes should be conditional on all variables that affect the probability of inclusion. We incorporate all the variables that are used in the weighting adjustment under the framework of multilevel regression and poststratification, as a byproduct generating model-based weights after smoothing. We improve small area estimation by dealing with different complex issues caused by real-life applications to obtain robust inference at finer levels for subdomains of interest. We investigate deep interactions and introduce structured prior distributions for smoothing and stability of estimates. The computation is done via Stan and is implemented in the open-source R package rstanarm and available for public use. We evaluate the design-based properties of the Bayesian procedure. Simulation studies illustrate how the model-based prediction and weighting inference can outperform classical weighting. We apply the method to the New York Longitudinal Study of Wellbeing. The new approach generates smoothed weights and increases efficiency for robust finite population inference, especially for subsets of the population.
Release date: 2020-12-15 - Articles and reports: 12-001-X202000200004Description:
This article proposes a weight scaling method for Firth’s penalized likelihood for proportional hazards regression models. The method derives a relationship between the penalized likelihood that uses scaled weights and the penalized likelihood that uses unscaled weights, and it shows that the penalized likelihood that uses scaled weights have some desirable properties. A simulation study indicates that the penalized likelihood using scaled weights produces smaller biases in point estimates and standard errors than the biases produced by the penalized likelihood using unscaled weights. The weighted penalized likelihood is applied to estimate hazard rates for heart attacks by using a public-use data set from the National Health and Epidemiology Followup Study (NHEFS). SAS® statements to estimate hazard rates using data from complex surveys are given in the appendix.
Release date: 2020-12-15 - 36-23-0001Description: Input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a “shock” to an IO model will show the direct, indirect and induced impacts on Gross Domestic Product (GDP), which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. The model also includes estimates of the impacts on energy use (expressed in terajoules) and greenhouse gas emissions (carbon dioxide equivalent, expressed in kilotonnes). IO price, energy, and tax models may also be available depending on the availability of resources. For more details, ask us for the Guide to using the input-output simulation model, available upon request.Release date: 2020-11-23
- Previous Go to previous page of All results
- 1 Go to page 1 of All results
- 2 Go to page 2 of All results
- 3 Go to page 3 of All results
- 4 (current) Go to page 4 of All results
- 5 Go to page 5 of All results
- 6 Go to page 6 of All results
- 7 Go to page 7 of All results
- ...
- 18 Go to page 18 of All results
- Next Go to next page of All results
Data (1)
Data (1) ((1 result))
- Public use microdata: 12M0022XDescription:
This package was designed to enable users to access and manipulate the microdata file for Cycle 22 (2008) of the General Social Survey (GSS). It contains information on the objectives, methodology and estimation procedures, as well as guidelines for releasing estimates based on the survey. Cycle 22 collected data from persons 15 years and over living in private households in Canada, excluding residents of the Yukon, Northwest Territories and Nunavut; and full-time residents of institutions. The survey covered a range of topics such as social networks, and social and civic participation. Information was also collected on major changes in respondents' lives in the last 12 months, the resources they used during these transitions and unmet needs for help. Questions were also asked on trust, sense of belonging, volunteering and unpaid work.
Release date: 2010-03-05
Analysis (150)
Analysis (150) (0 to 10 of 150 results)
- Articles and reports: 11-633-X2025005Description: This study presents an approach to model changes in the numbers of elementary, secondary and postsecondary students who are immigrants (including both permanent residents and non permanent residents) in response to changes in overall immigration levels.Release date: 2025-12-22
- Articles and reports: 12-001-X202500100007Description: We introduce a novel approach to model-assisted calibration estimation in survey sampling using generalized entropy. The method builds upon recent work by Kwon, Kim and Qiu (2024) and extends it to a model-assisted framework. Unlike traditional calibration techniques, this approach employs a generalized entropy function as the objective for optimization and incorporates a debiasing calibration constraint to ensure design consistency. The proposed estimator is shown to be asymptotically equivalent to an augmented generalized regression (GREG) estimator. It allows for unequal model variance, potentially improving efficiency when the sampling design is informative. The paper presents both design-based and model-based justifications for the method, along with asymptotic properties and variance estimation techniques. Computational aspects are discussed, including an unconstrained optimization approach that facilitates implementation, especially for high-dimensional auxiliary variables. The method’s performance is evaluated through a simulation study, demonstrating its effectiveness in improving estimation efficiency, particularly when the sampling design is informative.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100008Description: Tightened budgets, continuing decrease of response rates in traditional probability surveys and increasing pressure by users for more timely data, has stimulated research on the use of nonprobability sample data, such as administrative records, web scraping, mobile phone data and voluntary internet surveys, for inference on finite population parameters like means and totals. These data are often easier, faster and cheaper to collect than traditional probability samples. However, a major concern with the use of this kind of data for official statistics is their nonrepresentativeness due to possible selection bias, which if not accounted for properly, could bias the inference. In this article, we review and discuss methods considered in the literature to deal with this problem and propose new methods, distinguishing between methods based on integration of the nonprobability sample with an appropriate probability sample, and methods that base the inference solely on the nonprobability sample. Empirical illustrations, based on simulated data are provided.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100009Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100011Description: This discussion examines some advancements in survey design and estimation, inspired by the comprehensive appraisal of Professors Jon Rao and Sharon Lohr on current trends in the field. It delves into three specific areas: balanced sampling, calibration, and small area estimation. Probabilistic balanced sampling methods, such as the cube method and penalized balanced sampling, are explored, with an emphasis on addressing emerging challenges, including extensions to linear mixed models, nonparametric regression models, and spatially balanced designs. Calibration is discussed using a modular framework that incorporates modern regression techniques, and highlights innovative uses of model calibration for data editing and causal inference. Small area estimation is considered in the context of latent variable modeling and data integration, emphasizing its role when the variable(s) of interest cannot be measured either directly or without error. Applications in integrating probability and non-probability data and conducting causal analysis at local level are also discussed.Release date: 2025-06-30
- Articles and reports: 12-001-X202500100012Description: In this discussion, we complement the excellent overview by Profs. Lohr and Rao with some additional topics. The first topic is a call for more recognition of the central role of modeling in survey estimation. The second is a brief discussion of the use of partial frame information in survey design. Finally, we draw the attention to recent increases of synthetic methods, in particular, multilevel regression and poststratification (MRP) in small area estimation applications.Release date: 2025-06-30
- 7. Comments by Mary E. Thompson on “Progress in survey science and practice: Yesterday-today-tomorrow”Articles and reports: 12-001-X202500100016Description: These comments on C.-E. Särndal’s paper, “Progress in survey science and practice: yesterday-today-tomorrow”, will touch on probability sampling fundamentals, progress through competing approaches to inference, connections with other parts of statistics, and data in the twenty-first century.Release date: 2025-06-30
- Journals and periodicals: 11-632-XDescription: The newsletter offers information aimed at three main groups, businesses (small to medium), communities and ethno-cultural groups/communities. Articles and outreach materials will assist their understanding of national and local data from the many relevant sources found on the Statistics Canada website.Release date: 2025-01-16
- Stats in brief: 89-20-00062024003Description: 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
- Articles and reports: 11-522-X202200100017Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.Release date: 2024-06-28
- Previous Go to previous page of Analysis results
- 1 (current) Go to page 1 of Analysis results
- 2 Go to page 2 of Analysis results
- 3 Go to page 3 of Analysis results
- 4 Go to page 4 of Analysis results
- 5 Go to page 5 of Analysis results
- 6 Go to page 6 of Analysis results
- 7 Go to page 7 of Analysis results
- ...
- 15 Go to page 15 of Analysis results
- Next Go to next page of Analysis results
Reference (25)
Reference (25) (0 to 10 of 25 results)
- 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
- Notices and consultations: 95-635-XDescription: To stay relevant, preparing for a new Census of Agriculture requires a thorough evaluation of data requirements. Before each census, Statistics Canada conducts consultations to solicit input and feedback on the Census of Agriculture's content. This report describes those consultations and the process that was followed to test and determine which topics could be potentially retained for the next census.Release date: 2024-11-27
- Surveys and statistical programs – Documentation: 11-633-X2024001Description: 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
- Surveys and statistical programs – Documentation: 84-538-XGeography: CanadaDescription: This electronic publication presents the methodology underlying the production of the life tables for Canada, provinces and territories.Release date: 2023-08-28
- Surveys and statistical programs – Documentation: 11-633-X2022009Description: 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 - Surveys and statistical programs – Documentation: 98-304-XDescription: The Guide to the Census of Population is a reference document that describes the various phases of the 2021 Census of Population. The guide provides an overview of content determination, sampling design, collection, data processing, data quality assessment, confidentiality guidelines and dissemination. It also includes response rates and other data quality information. This product may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2021 Census of Population.
The Guide to the Census of Population combines information previously available in the Overview of the Census, National Household Survey User Guide and the Data Quality and Confidentiality Standards and Guidelines from 2011.
Release date: 2022-11-30 - Surveys and statistical programs – Documentation: 11-633-X2021008Description: 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. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. 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: 2021-12-06
- Surveys and statistical programs – Documentation: 11-633-X2021002Description:
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. The IMDB includes Immigration, Refugees and Citizenship Canada (IRCC) administrative records which contain exhaustive information about immigrants who were admitted to Canada since 1952. It also includes data about non-permanent residents who have been issued temporary resident permits since 1980. 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: 2021-02-01 - Surveys and statistical programs – Documentation: 75F0002M2020001Description:
This note provides the definition of a first-time homebuyer concept used in the 2018 Canadian Housing Survey (CHS). It also includes the methodology used to identify first-time homebuyers and provides sensitivity analysis under alternative methodologies.
Release date: 2020-01-15 - Surveys and statistical programs – Documentation: 15F0004XDescription:
The input-output (IO) models are generally used to simulate the economic impacts of an expenditure on a given basket of goods and services or the output of one or several industries. The simulation results from a "shock" to an IO model will show the direct, indirect and induced impacts on GDP, which industries benefit the most, the number of jobs created, estimates of indirect taxes and subsidies generated, etc. For more details, ask us for the Guide to using the input-output simulation model, available free of charge upon request.
At various times, clients have requested the use of IO price, energy, tax and market models. Given their availability, arrangements can be made to use these models on request.
The national IO model was not released in 2015 or 2016.
Release date: 2019-04-04