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All (24,386)

All (24,386) (24,250 to 24,260 of 24,386 results)

24,251. Financial market statistics from the Toronto Stock Exchange
Surveys and statistical programs – Documentation: 5268
Description: The information pertains to financial market statistics of publicly-traded entities listed on the Toronto Stock Exchange.
24,252. Canadian Housing Survey
Surveys and statistical programs – Documentation: 5269
Description: This survey collects information about housing needs and experiences from a sample of Canadian households. Information is collected on core housing need, dwelling and neighbourhood satisfaction, housing moves or intentions to move, and other aspects of well-being related to housing.
24,253. Aboriginal Peoples Survey - Nunavut Inuit Supplement
Surveys and statistical programs – Documentation: 5270
Description: The purpose of the Aboriginal Peoples Survey - Nunavut Inuit Supplement is to learn more about the availability, interest and level of preparedness of Nunavut Inuit for government employment.
24,254. Survey on Home Health Care and Related Services
Surveys and statistical programs – Documentation: 5271
Description: This survey collects the financial and operating data needed to develop national and regional economic policies and programs.
24,255. Medical Assistance in Dying, 2019 and 2020
Surveys and statistical programs – Documentation: 5273
Description: The data is based on reports from physicians and nurse practitioners on written requests for and provisions of Medical Assistance in Dying (MAID) across Canada for the 2019, 2020 and 2021 calendar years.
24,256. The Canadian Index of Multiple Deprivation
Surveys and statistical programs – Documentation: 5274
Description: The purpose of the Canadian Index of Multiple Deprivation is to illustrate differences in deprivation between areas, and to better understand inequalities in various measures of socio-economic characteristics for geographical areas or population groups.
24,257. Producer Deliveries of Major Grains, Canada and selected provinces
Surveys and statistical programs – Documentation: 5275
Description: The purpose of this program is to collect data on licensed and unlicensed producer deliveries of major grains.
24,258. Alberta Spatial Price Index
Surveys and statistical programs – Documentation: 5276
Description: Statistics Canada is undertaking this survey to collect retail prices in 35 Alberta communities for the production of price indexes. These price indexes will estimate the difference in the retail cost of an identical (or very similar) group of products in each community and the cost of this same group of products in Edmonton.
24,259. Survey on Individual Safety in the Postsecondary Student Population
Surveys and statistical programs – Documentation: 5279
Description: The primary objective of this survey is to better understand how Canadian students perceive their personal safety in the school-related environment, as well as their experiences of victimization in this setting. The information will be used by governments to develop and implement programs and policies to help Canadian postsecondary students.
24,260. Wastewater-based estimates of drug consumption
Surveys and statistical programs – Documentation: 5280
Description: To estimate loads of drug metabolites in municipal wastewater as well as drug consumption of municipal populations for target drugs, based on the analysis of municipal wastewater.

Data (12,031)

Data (12,031) (30 to 40 of 12,031 results)

31. 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
32. 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
33. 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
34. 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
35. 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
36. 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
37. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Household operations, furnishings and equipment
Table: 18-10-0004-05
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 household operations, furnishings and equipment 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
38. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Clothing and footwear
Table: 18-10-0004-06
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 clothing and footwear 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
39. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Transportation
Table: 18-10-0004-07
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 transportation 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
40. Consumer Price Index, monthly, percentage change, not seasonally adjusted, Canada, provinces, Whitehorse and Yellowknife — Health and personal care
Table: 18-10-0004-08
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 health and personal care 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 (9,990)

Analysis (9,990) (10 to 20 of 9,990 results)

11. 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
12. 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
13. 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
14. 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
15. 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
16. 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
17. 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
18. 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
19. 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
20. 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

Reference (1,891)

Reference (1,891) (0 to 10 of 1,891 results)

1. Census Subdivision Boundary File, Reference Guide
Geographic files and documentation: 92-162-G
Description: This reference guide is intended for users of the Census Subdivisions Boundary File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.
Release date: 2024-06-26
2. Census Subdivision Boundary File
Geographic files and documentation: 92-162-X
Description: The Census Subdivision Boundary File contains the boundaries of all census subdivisions which combined cover all of Canada. A census subdivision is a municipality or an area treated as an equivalent to a municipality for statistical purposes (for example, Indian reserves and unorganized territories). The file provides a framework for mapping and spatial analysis using commercially available geographic information systems (GIS) or other mapping software.

The Census Subdivision Boundary File is portrayed in Lambert conformal conic projection and is based on the North American Datum of 1983 (NAD83). A reference guide is available (92-162-G).
Release date: 2024-06-26
3. Road Network File, Reference Guide
Geographic files and documentation: 92-500-G
Description: This reference guide is intended for users of the Road Network File. The guide provides an overview of the file, the general methodology used to create it, and important technical information for users.
Release date: 2024-06-26
4. Road Network File
Geographic files and documentation: 92-500-X
Geography: Canada
Description: The Road Network File (RNF) is a digital representation of Canada's national road network, containing information such as street names, types, directions and address ranges. The information comes from the National Geographic Database (NGD).

A reference guide is available (92-500-G).
Release date: 2024-06-26
5. Interim List of Changes to Municipal Boundaries, Status, and Names
Notices and consultations: 92F0009X
Description: This report provides a summary of changes to municipal boundaries, status and names. The list is usually produced on an annual basis for changes that occurred during the previous year. A five year list is produced on Census of population years.
Release date: 2024-06-26
6. Population Projections for Canada, Provinces and Territories: Technical Report on Methodology and Assumptions
Surveys and statistical programs – Documentation: 91-620-X
Description: This report aims to describe the methods used for the calculation of projection parameters, the various projection assumptions and their rationales.
Release date: 2024-06-24
7. Guide to the Job Vacancy and Wage Survey, 2024
Surveys and statistical programs – Documentation: 75-514-G2024001
Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality.
Release date: 2024-06-18
8. Guide to the Job Vacancy and Wage Survey
Surveys and statistical programs – Documentation: 75-514-G
Description: The Guide to the Job Vacancy and Wage Survey contains a dictionary of concepts and definitions, and covers topics such as survey methodology, data collection, processing, and data quality. The guide covers both components of the survey: the job vacancy component, which is quarterly, and the wage component, which is annual.
Release date: 2024-06-18
9. Latest Developments in the Canadian Economic Accounts
Notices and consultations: 13-605-X
Description: 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: 2024-06-05
10. Regional Discussion Report: Review of First Nations, Métis and Inuit questions for the 2026 Census of Population
Notices and consultations: 41-20-00012024001
Description: From November 2022 to March 2023 Statistics Canada undertook a series of discussions to obtain feedback on the questions used to identify First Nations people, Métis and Inuit on the Census of Population and on other Statistics Canada surveys. This report summarizes the feedback received during these discussions.
Release date: 2024-05-29

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