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All (24,373) (0 to 10 of 24,373 results)

  • 1. Authors’ response to comments on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”: Some new developments on likelihood approaches to estimation of participation probabilities for non-probability samples
    Articles and reports: 12-001-X202400100001
    Description: Inspired by the two excellent discussions of our paper, we offer some new insights and developments into the problem of estimating participation probabilities for non-probability samples. First, we propose an improvement of the method of Chen, Li and Wu (2020), based on best linear unbiased estimation theory, that more efficiently leverages the available probability and non-probability sample data. We also develop a sample likelihood approach, similar in spirit to the method of Elliott (2009), that properly accounts for the overlap between both samples when it can be identified in at least one of the samples. We use best linear unbiased prediction theory to handle the scenario where the overlap is unknown. Interestingly, our two proposed approaches coincide in the case of unknown overlap. Then, we show that many existing methods can be obtained as a special case of a general unbiased estimating function. Finally, we conclude with some comments on nonparametric estimation of participation probabilities.
    Release date: 2024-06-25
  • 2. Comments by Changbao Wu on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”
    Articles and reports: 12-001-X202400100002
    Description: We provide comparisons among three parametric methods for the estimation of participation probabilities and some brief comments on homogeneous groups and post-stratification.
    Release date: 2024-06-25
  • 3. Comments by Julie Gershunskaya and Vladislav Beresovsky on “Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data”
    Articles and reports: 12-001-X202400100003
    Description: Beaumont, Bosa, Brennan, Charlebois and Chu (2024) propose innovative model selection approaches for estimation of participation probabilities for non-probability sample units. We focus our discussion on the choice of a likelihood and parameterization of the model, which are key for the effectiveness of the techniques developed in the paper. We consider alternative likelihood and pseudo-likelihood based methods for estimation of participation probabilities and present simulations implementing and comparing the AIC based variable selection. We demonstrate that, under important practical scenarios, the approach based on a likelihood formulated over the observed pooled non-probability and probability samples performed better than the pseudo-likelihood based alternatives. The contrast in sensitivity of the AIC criteria is especially large for small probability sample sizes and low overlap in covariates domains.
    Release date: 2024-06-25
  • 4. Handling non-probability samples through inverse probability weighting with an application to Statistics Canada’s crowdsourcing data
    Articles and reports: 12-001-X202400100004
    Description: Non-probability samples are being increasingly explored in National Statistical Offices as an alternative to probability samples. However, it is well known that the use of a non-probability sample alone may produce estimates with significant bias due to the unknown nature of the underlying selection mechanism. Bias reduction can be achieved by integrating data from the non-probability sample with data from a probability sample provided that both samples contain auxiliary variables in common. We focus on inverse probability weighting methods, which involve modelling the probability of participation in the non-probability sample. First, we consider the logistic model along with pseudo maximum likelihood estimation. We propose a variable selection procedure based on a modified Akaike Information Criterion (AIC) that properly accounts for the data structure and the probability sampling design. We also propose a simple rank-based method of forming homogeneous post-strata. Then, we extend the Classification and Regression Trees (CART) algorithm to this data integration scenario, while again properly accounting for the probability sampling design. A bootstrap variance estimator is proposed that reflects two sources of variability: the probability sampling design and the participation model. Our methods are illustrated using Statistics Canada’s crowdsourcing and survey data.
    Release date: 2024-06-25
  • 5. Author’s response to comments on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”
    Articles and reports: 12-001-X202400100005
    Description: In this rejoinder, I address the comments from the discussants, Dr. Takumi Saegusa, Dr. Jae-Kwang Kim and Ms. Yonghyun Kwon. Dr. Saegusa’s comments about the differences between the conditional exchangeability (CE) assumption for causal inferences versus the CE assumption for finite population inferences using nonprobability samples, and the distinction between design-based versus model-based approaches for finite population inference using nonprobability samples, are elaborated and clarified in the context of my paper. Subsequently, I respond to Dr. Kim and Ms. Kwon’s comprehensive framework for categorizing existing approaches for estimating propensity scores (PS) into conditional and unconditional approaches. I expand their simulation studies to vary the sampling weights, allow for misspecified PS models, and include an additional estimator, i.e., scaled adjusted logistic propensity estimator (Wang, Valliant and Li (2021), denoted by sWBS). In my simulations, it is observed that the sWBS estimator consistently outperforms or is comparable to the other estimators under the misspecified PS model. The sWBS, as well as WBS or ABS described in my paper, do not assume that the overlapped units in both the nonprobability and probability reference samples are negligible, nor do they require the identification of overlap units as needed by the estimators proposed by Dr. Kim and Ms. Kwon.
    Release date: 2024-06-25
  • 6. Comments by Takumi Saegusa on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”: Causal inference, non-probability sample, and finite population
    Articles and reports: 12-001-X202400100006
    Description: In some of non-probability sample literature, the conditional exchangeability assumption is considered to be necessary for valid statistical inference. This assumption is rooted in causal inference though its potential outcome framework differs greatly from that of non-probability samples. We describe similarities and differences of two frameworks and discuss issues to consider when adopting the conditional exchangeability assumption in non-probability sample setups. We also discuss the role of finite population inference in different approaches of propensity scores and outcome regression modeling to non-probability samples.
    Release date: 2024-06-25
  • 7. Comments by Jae Kwang Kim and Yonghyun Kwon on “Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples”
    Articles and reports: 12-001-X202400100007
    Description: Pseudo weight construction for data integration can be understood in the two-phase sampling framework. Using the two-phase sampling framework, we discuss two approaches to the estimation of propensity scores and develop a new way to construct the propensity score function for data integration using the conditional maximum likelihood method. Results from a limited simulation study are also presented.
    Release date: 2024-06-25
  • 8. Exchangeability assumption in propensity-score based adjustment methods for population mean estimation using non-probability samples
    Articles and reports: 12-001-X202400100008
    Description: Nonprobability samples emerge rapidly to address time-sensitive priority topics in different areas. These data are timely but subject to selection bias. To reduce selection bias, there has been wide literature in survey research investigating the use of propensity-score (PS) adjustment methods to improve the population representativeness of nonprobability samples, using probability-based survey samples as external references. Conditional exchangeability (CE) assumption is one of the key assumptions required by PS-based adjustment methods. In this paper, I first explore the validity of the CE assumption conditional on various balancing score estimates that are used in existing PS-based adjustment methods. An adaptive balancing score is proposed for unbiased estimation of population means. The population mean estimators under the three CE assumptions are evaluated via Monte Carlo simulation studies and illustrated using the NIH SARS-CoV-2 seroprevalence study to estimate the proportion of U.S. adults with COVID-19 antibodies from April 01-August 04, 2020.
    Release date: 2024-06-25
  • 9. Authors’ response to comments on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
    Articles and reports: 12-001-X202400100009
    Description: Our comments respond to discussion from Sen, Brick, and Elliott. We weigh the potential upside and downside of Sen’s suggestion of using machine learning to identify bogus respondents through interactions and improbable combinations of variables. We join Brick in reflecting on bogus respondents’ impact on the state of commercial nonprobability surveys. Finally, we consider Elliott’s discussion of solutions to the challenge raised in our study.
    Release date: 2024-06-25
  • 10. Comments by Aditi Sen on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
    Articles and reports: 12-001-X202400100010
    Description: This discussion summarizes the interesting new findings around measurement errors in opt-in surveys by Kennedy, Mercer and Lau (KML). While KML enlighten readers about “bogus responding” and possible patterns in them, this discussion suggests combining these new-found results with other avenues of research in nonprobability sampling, such as improvement of representativeness.
    Release date: 2024-06-25
Data (12,024)

Data (12,024) (0 to 10 of 12,024 results)

  • 1. Food Services and Drinking Places Sales
    Data Visualization: 71-607-X2017003
    Description: This web application provides access to data on the sales of food services and drinking places for Canada, provinces and territories. This dynamic application allows users to compare provincial and territorial data with interactive maps and charts. All data in this release are seasonally adjusted and expressed in current dollars.
    Release date: 2024-06-25
  • 2. Consumer Price Index Data Visualization Tool
    Data Visualization: 71-607-X2018016
    Description: This interactive dashboard provides access to current and historical Consumer Price Index (CPI) data in a dynamic and customizable format. Key indicators such as the 12-month and 1-month inflation rates and price trends are presented in interactive charts, allowing users to compare and analyze price changes of all the goods and services in the CPI basket over time as well as across geography (national, provincial and territorial levels).

    Other CPI indicators available in this tool include the Bank of Canada’s core measures of inflation, seasonally adjusted inflation rates, and CPI basket weights.

    This web-based application is updated monthly, as soon as the data for the latest reference month is released in The Daily.

    Release date: 2024-06-25
  • 3. Statistics Canada - Data Visualization Products
    Table: 71-607-X
    Description: Statistics Canada produces a variety of interactive visualization tools that present data in a graphical form. These tools provide a useful way of interpreting trends behind our data on various social and economic topics.
    Release date: 2024-06-25
  • 4. Statement of government operations and balance sheet, government finance statistics
    Table: 10-10-0015-01
    Geography: Canada
    Frequency: Quarterly
    Description: Quarterly data by level of government.
    Release date: 2024-06-25
  • 5. Bank of Canada, money market and other interest rates
    Table: 10-10-0139-01
    Geography: Canada
    Frequency: Daily
    Description: This table contains 39 series, with data for starting from 1991 (not all combinations necessarily have data for all years). This table contains data described by the following dimensions (Not all combinations are available): Geography (1 item: Canada); Financial market statistics (39 items: Government of Canada Treasury Bills, 1-month (composite rates); Government of Canada Treasury Bills, 2-month (composite rates); Government of Canada Treasury Bills, 3-month (composite rates);Government of Canada Treasury Bills, 6-month (composite rates); ...).
    Release date: 2024-06-25
  • 6. Monthly average retail prices for gasoline and fuel oil, by geography
    Table: 18-10-0001-01
    Geography: Canada, Census subdivision, Census metropolitan area, Census metropolitan area part
    Frequency: Monthly
    Description:

    Monthly average retail prices for gasoline and fuel oil for Canada, selected provincial cities, Whitehorse and Yellowknife. Prices are presented for the current month and previous four months. Includes fuel type and the price in cents per litre.

    Release date: 2024-06-25
  • 7. Consumer Price Index, monthly, not seasonally adjusted
    Table: 18-10-0004-01
    Geography: Canada, Province or territory, Census subdivision, Census metropolitan area, Census metropolitan area part
    Frequency: Monthly
    Description:

    Monthly indexes for major components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the current month and previous four months. The base year for the index is 2002=100.

    Release date: 2024-06-25
  • 8. Consumer Price Index by geography, all-items, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse, Yellowknife and Iqaluit
    Table: 18-10-0004-02
    Geography: Canada, Province or territory, Census subdivision, Census metropolitan area, Census metropolitan area part
    Frequency: Monthly
    Description:

    Monthly indexes and percentage changes for all components and special aggregates of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse, Yellowknife and Iqaluit. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100. 

    Release date: 2024-06-25
  • 9. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Food
    Table: 18-10-0004-03
    Geography: Canada, Province or territory, Census subdivision, Census metropolitan area, Census metropolitan area part
    Frequency: Monthly
    Description: Monthly indexes and percentage changes for selected sub-groups of the food component of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse and Yellowknife. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.
    Release date: 2024-06-25
  • 10. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Shelter
    Table: 18-10-0004-04
    Geography: Canada, Province or territory, Census subdivision, Census metropolitan area, Census metropolitan area part
    Frequency: Monthly
    Description: Monthly indexes and percentage changes for selected sub-groups of the shelter component of the Consumer Price Index (CPI), not seasonally adjusted, for Canada, provinces, Whitehorse and Yellowknife. Data are presented for the corresponding month of the previous year, the previous month and the current month. The base year for the index is 2002=100.
    Release date: 2024-06-25
Analysis (9,984)

Analysis (9,984) (20 to 30 of 9,984 results)

  • 21. Quality of early-career employment for Indigenous graduates with a bachelor’s degree
    Stats in brief: 11-627-M2024029
    Description: The infographic uses data from the integrated file of the Postsecondary Student Information System, the 2016 Census, the 2021 Census and the T1 Family File to compare the job quality of Indigenous graduates with a bachelor's degree with that of non-racialized and non-Indigenous graduates two years after graduation. Job quality indicators include employment income, unionization rate, and employer pension plan coverage rate.
    Release date: 2024-06-24
  • 22. Natural resource indicators first quarter 2024
    Stats in brief: 11-001-X202417616361
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-24
  • 23. Population projections: Canada, provinces and territories 2023 to 2073
    Stats in brief: 11-001-X20241764039
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-24
  • 24. Industrial product and raw materials price indexes May 2024
    Stats in brief: 11-001-X20241733556
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-21
  • 25. Retail trade April 2024
    Stats in brief: 11-001-X20241733660
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-21
  • 26. Employment Insurance April 2024
    Stats in brief: 11-001-X20241723537
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-06-20
  • 27. Analysis on artificial intelligence use by businesses in Canada, second quarter of 2024
    Articles and reports: 11-621-M2024008
    Description: This article explores results from the survey related to the use of AI in producing goods and delivering services. Furthermore, this article explains the specific types of AI being used, such as machine learning, virtual agents and voice recognition, as well as the impact of AI adoption on tasks performed by employees and on employment levels. It involves an examination of the data produced by the Canadian Survey on Business Conditions.
    Release date: 2024-06-20
  • 28. International postsecondary students in Canada: 2020 graduates
    Stats in brief: 11-627-M2024027
    Description: This infographic provides details about the number of graduates and median employment income two years after graduation for international postsecondary students, by educational qualification and field of study.
    Release date: 2024-06-20
  • 29. Analysis in Brief
    Journals and periodicals: 11-621-M
    Geography: Canada
    Description: The papers published in the Analysis in Brief analytical series shed light on current economic issues. Aimed at a general audience, they cover a wide range of topics including National Accounts, business enterprises, trade, transportation, agriculture, the environment, manufacturing, science and technology, services, etc.
    Release date: 2024-06-20
  • 30. The impacts of extreme heat events on non-accidental, cardiovascular, and respiratory mortality: An analysis of 12 Canadian cities from 2000 to 2020
    Articles and reports: 82-003-X202400600001
    Description: Extreme heat has significant impacts on mortality. In Canada, past research has analyzed the degree to which non-accidental mortality increases during single extreme heat events; however, few studies have considered multiple causes of death and the impacts of extreme heat events on mortality over longer time periods. This study analyzes the impacts of extreme heat events on nonaccidental, cardiovascular, and respiratory deaths from 2000 to 2020 in 12 of the largest cities in Canada.
    Release date: 2024-06-19
Reference (1,891)

Reference (1,891) (10 to 20 of 1,891 results)

  • 11. Guide to the Survey of Employment, Payrolls and Hours
    Surveys and statistical programs – Documentation: 72-203-G
    Description: The Guide to the Survey of Employment, Payrolls and Hours contains a dictionary of concepts and definitions and covers topics such as survey methodology, data collection and processing, and data quality. It also provides information on products and services, as well as the survey questionnaire.
    Release date: 2024-03-28
  • 12. Education Indicators in Canada: Handbook for the Report of the Pan-Canadian Education Indicators Program
    Surveys and statistical programs – Documentation: 81-582-G
    Description: This handbook complements the tables of the Pan-Canadian Education Indicators Program (PCEIP). It is a guide that provides general descriptions for each indicator and indicator component. PCEIP has five broad indicator sets: a portrait of the school-age population; financing education systems; elementary and secondary education; postsecondary education; and transitions and outcomes.

    The Pan-Canadian Education Indicators Program (PCEIP) is a joint venture of Statistics Canada and the Council of Ministers of Education, Canada.

    Release date: 2024-03-28
  • 13. Health Regions: Boundaries and Correspondence with Census Geography
    Geographic files and documentation: 82-402-X
    Description: Health regions are defined by the provinces and represent administrative areas or regions of interest to health authorities. This product contains correspondence files (linking health regions to latest Census geographic codes) and digital boundary files. User documentation provides an overview of health regions, sources, methods, limitations and product description (file format and layout).

    In addition to the geographic files, this product also includes Census data (basic profile) for health regions.

    Release date: 2024-03-27
  • 14. Reference guide on the social inclusion indicators for ethnocultural groups in Canada, 2024
    Surveys and statistical programs – Documentation: 89-657-X2024002
    Description: This document presents a complete list of the social inclusion indicators for ethnocultural groups in Canada that are available on the homepage of our Gender, Diversity and Inclusion Statistics Hub. The information provided for each indicator includes a short description of the corresponding derivation, available data sources, reference years and accessible levels of geographical and disaggregation. Each indicator has a corresponding products number (data tables, visualization tools and analytical documents). This document has been updated to reflect the social inclusion indicators and associated products that are available in 2024.
    Release date: 2024-03-26
  • 15. Study on the Underclassification of Children Eligible for Instruction in the Minority Official Language in the 2021 Census
    Surveys and statistical programs – Documentation: 98-26-0008
    Description: This report presents the results of a study on the estimated number of children eligible for instruction in the minority official language, pursuant to section 23 of the Canadian Charter of Rights and Freedoms, who were classified as ineligible in the 2021 Census because relationships between family members living at different addresses could not be established within this data source. Using other data sources, including previous censuses and administrative data (such as vital statistics and tax data), we were able to establish these family relationships within the 2021 Census. This report presents the methods and data sources used first, then the results by selected regions and age groups.
    Release date: 2024-03-26
  • 16. Indigenous Peoples Technical Report, Census of Population
    Surveys and statistical programs – Documentation: 98-307-X
    Description:

    This report deals with Indigenous identity, Indigenous ancestry, Indigenous group, Registered or Treaty Indian status, Membership in a First Nation or Indian band, Membership in a Métis organization or Settlement, and Enrollment under an Inuit land claims agreement, and contains explanations of concepts, data quality, historical comparability and comparability with other sources, as well as information on data collection, processing and dissemination.

    Release date: 2024-03-20
  • 17. Technical Reference Guide for the Preliminary Estimates from the T1 Family File (T1FF)
    Surveys and statistical programs – Documentation: 11-26-0001
    Description: The data for the products associated with this technical reference guide are derived from an early version of the T1 file that Statistics Canada receives from Canada Revenue Agency (CRA). Data on special topics linked to income and income tax deductions can be derived from the T1 income tax returns. Topics of interest for this preliminary release of the T1 data can vary from year to year.
    Release date: 2024-03-06
  • 18. Census of Agriculture: Data quality report
    Surveys and statistical programs – Documentation: 32-26-0007
    Description: Census of Agriculture data provide statistical information on farms and farm operators at fine geographic levels and for small subpopulations. Quality evaluation activities are essential to ensure that census data are reliable and that they meet user needs.

    This report provides data quality information pertaining to the Census of Agriculture, such as sources of error, error detection, disclosure control methods, data quality indicators, response rates and collection rates.
    Release date: 2024-02-06
  • 19. Guide to Canadian International Merchandise Trade Statistics
    Surveys and statistical programs – Documentation: 13-605-X202400100001
    Description: This guide presents information to enhance an understanding of Canadian International Merchandise Trade statistics. It provides essential definitions, describes key concepts and methodology, and outlines data processes. An overview of the published data, including descriptions of product, industry, and geographical classifications, is provided along with links to the products where these data are available.
    Release date: 2024-01-22
  • 20. User Guide and Data Dictionary for Preliminary COVID-19 Data
    Surveys and statistical programs – Documentation: 13-26-0002
    Description:

    Created in collaboration with the Public Health Agency of Canada (PHAC), this user guide with appended data dictionary provides Canadians and researchers with required information to be able to utilize the Detailed preliminary information on confirmed cases of COVID-19 (Revised) table.

    The user guide with appended data dictionary describes background information of COVID-19 as well as objectives, coverage, content, limitations and data quality concerns of the table.

    Release date: 2024-01-12
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