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All (24,389) (50 to 60 of 24,389 results)

51. Financial market statistics, as at Tuesday, Bank of Canada
Table: 10-10-0144-01
Geography: Canada
Frequency: Weekly
Description: This table contains 8 series, with data starting from 1992 (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), Rates (8 items: Bank rate; Treasury bill auction - average yields: 3 month; Treasury bill auction - average yields: 6 month; Treasury bill auction - average yields: 1 year; ...).
Release date: 2024-06-27
52. Selected characteristics of tax filers and dependants, income and demographics (final T1 Family File)
Table: 11-10-0004-01
Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants, summary table, income and demographics (final T1 Family File; T1FF).
Release date: 2024-06-27
53. Tax filers and dependants by sex, marital status and age
Table: 11-10-0005-01
Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants by sex, marital status and age groups (final T1 Family File; T1FF).
Release date: 2024-06-27
54. Tax filers and dependants by single years of age
Table: 11-10-0006-01
Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants by sex and single years of age (final T1 Family File; T1FF).
Release date: 2024-06-27
55. Tax filers and dependants with income by source of income
Table: 11-10-0007-01
Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants with income by source of income (final T1 Family File; T1FF).
Release date: 2024-06-27
56. Tax filers and dependants with income by total income, sex and age
Table: 11-10-0008-01
Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants by total income, sex and age groups (final T1 Family File; T1FF).
Release date: 2024-06-27
57. Selected income characteristics of census families by family type
Table: 11-10-0009-01
Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Families of tax filers; Selected income characteristics of census families by family type (final T1 Family File; T1FF).
Release date: 2024-06-27
58. Tax filers and dependants by census family type and age
Table: 11-10-0010-01
Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Individuals; Tax filers and dependants by census family type and age groups (final T1 Family File; T1FF).
Release date: 2024-06-27
59. Census families by age of older partner or parent and number of children
Table: 11-10-0011-01
Geography: Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Families of tax filers; Census families by age of older partner or parent and number of children (final T1 Family File; T1FF).
Release date: 2024-06-27
60. Distribution of total income by census family type and age of older partner, parent or individual
Table: 11-10-0012-01
Geography: Canada, Province or territory, Census metropolitan area, Census agglomeration, Census metropolitan area part, Census agglomeration part
Frequency: Annual
Description: Families of tax filers; Distribution of total income by census family type and age of older partner, parent or individual (final T1 Family File; T1FF).
Release date: 2024-06-27

Data (12,031)

Data (12,031) (0 to 10 of 12,031 results)

1. Real-time Local Business Conditions Index
Data Visualization: 71-607-X2021017
Description: The need for alternative data sources is of growing importance for both supplementing Statistics Canada's data holdings and for nowcasting economic activity. In response to this need, Statistics Canada initiated the development of a Real-time Local Business Conditions Index (RT-LBCI). The index brings together data from a few different sources, including Google's Places API (containing data on temporary and permanent businesses closures), TomTom Real-time traffic API (road traffic data), as well as information from Statistics Canada data holdings (monthly retail and wholesale, Business Register, etc.). The project aims to compute a near real-time index of economic activity in Canadian major cities.
Release date: 2024-06-28
2. National Address Register
Profile of a community or region: 46-26-0002
Description: 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: 2024-06-28
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: 2024-06-28
4. Financial market statistics, last Wednesday unless otherwise stated, Bank of Canada
Table: 10-10-0122-01
Geography: Canada
Frequency: Monthly
Description: This table contains 71 series, with data starting from 1934 (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 items: Canada ...), Rates (71 items: Bank rate; last Tuesday or last Thursday; Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate ...).
Release date: 2024-06-28
5. Selected United States dollar interest rates, Wednesdays, Bank of Canada
Table: 10-10-0138-01
Frequency: Weekly
Description: This table contains 12 series, with data starting from 1954 (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: United States); Rates (12 items: Federal Reserve Bank of New York - discount rate; Prime rate charged by banks; Federal funds rate;Commercial paper, adjusted: 1 month; ...).
Release date: 2024-06-28
6. 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: 2024-06-28
7. Fisher commodity price index, United States dollar terms, Bank of Canada, Fisher commodity price index, United States dollar terms, Bank of Canada, weekly
Table: 10-10-0143-01
Geography: Canada
Frequency: Weekly
Description: This table contains 7 series, with data starting from 1972 (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), Commodity (7 items: Total, all commodities; Total excluding energy; Energy; Metals and Minerals; ...).
Release date: 2024-06-28
8. Financial market statistics, as at Wednesday, Bank of Canada
Table: 10-10-0145-01
Geography: Canada
Frequency: Weekly
Description: This table contains 38 series, with data starting from 1957 (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), Rates (38 items: Bank rate; Chartered bank administered interest rates - prime business; Chartered bank - consumer loan rate; Forward premium or discount (-), United States dollars in Canada: 1 month; ...).
Release date: 2024-06-28
9. Financial Soundness Indicators, Canada
Table: 10-10-0146-01
Geography: Canada
Frequency: Quarterly
Description:
This table includes six Financial Soundness Indicators for Canada as provided by the Bank of Canada. These Indicators are compiled and disseminated with other Indicators as part of the Special Data Dissemination Standard Plus from the International Monetary Fund.
Release date: 2024-06-28
10. Tobacco, sales and inventories, monthly production
Table: 16-10-0044-01
Geography: Canada
Frequency: Monthly
Description: Tobacco products (cigarettes, cigars, manufactured tobacco, fine cut, manufactured tobacco, pipe tobacco), monthly production, sales (total, domestic, to ships, air stores and foreign embassies in Canada) and inventories for Canada.
Release date: 2024-06-28

Analysis (9,992)

Analysis (9,992) (20 to 30 of 9,992 results)

21. 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
22. 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
23. 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
24. 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
25. 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
26. 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
27. 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
28. Comments by Michael R. Elliott on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
Articles and reports: 12-001-X202400100011
Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.
Release date: 2024-06-25
29. Comments by J. Michael Brick on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
Articles and reports: 12-001-X202400100012
Description: Nonprobability samples are quick and low-cost and have become popular for some types of survey research. Kennedy, Mercer and Lau examine data quality issues associated with opt-in nonprobability samples frequently used in the United States. They show that the estimates from these samples have serious problems that go beyond representativeness. A total survey error perspective is important for evaluating all types of surveys.
Release date: 2024-06-25
30. Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith
Articles and reports: 12-001-X202400100013
Description: Statistical approaches developed for nonprobability samples generally focus on nonrandom selection as the primary reason survey respondents might differ systematically from the target population. Well-established theory states that in these instances, by conditioning on the necessary auxiliary variables, selection can be rendered ignorable and survey estimates will be free of bias. But this logic rests on the assumption that measurement error is nonexistent or small. In this study we test this assumption in two ways. First, we use a large benchmarking study to identify subgroups for which errors in commercial, online nonprobability samples are especially large in ways that are unlikely due to selection effects. Then we present a follow-up study examining one cause of the large errors: bogus responding (i.e., survey answers that are fraudulent, mischievous or otherwise insincere). We find that bogus responding, particularly among respondents identifying as young or Hispanic, is a significant and widespread problem in commercial, online nonprobability samples, at least in the United States. This research highlights the need for statisticians working with commercial nonprobability samples to address bogus responding and issues of representativeness – not just the latter.
Release date: 2024-06-25

Reference (1,892)

Reference (1,892) (60 to 70 of 1,892 results)

61. Census Content Consultation Guide
Notices and consultations: 92-136-G
Description:
As is the case in advance of each Census, content consultations are being held with data users. The Census Content Consultation Guide gives you the opportunity to provide input.

Release date: 2023-01-09
62. Income Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021004
Description: This reference guide provides information to help users effectively use and interpret income data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-12-15
63. Education Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021013
Description: This reference guide provides information to help users effectively use and interpret education data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-12-01
64. Guide to the Census of Population, 2021
Surveys and statistical programs – Documentation: 98-304-X2021001
Description: 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.
Release date: 2022-11-30
65. Census Dictionary
Surveys and statistical programs – Documentation: 98-301-X
Description: The Census Dictionary is a reference document which contains detailed definitions of Census of Population concepts, variables and geographic terms, as well as historical information.
By referring to the Census Dictionary, both beginner and intermediate data users will gain a better understanding of the data and how to compare variables between census years.

The Census Dictionary will be released iteratively starting with geography and non-data dependent topic definitions, tables, figures and appendices with additional content made available based on subsequent topic releases.
Release date: 2022-11-30
66. Guide to the Census of Population
Surveys and statistical programs – Documentation: 98-304-X
Description:
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
67. Education Reference Guide, Census of Population, 2016
Surveys and statistical programs – Documentation: 98-500-X2016013
Description:
This guide focuses on the following topic: education. This reference guide provides information that enables users to effectively use, apply and interpret data from the 2016 Census. This guide contains definitions and explanations of concepts, classifications, data quality and comparability to other sources. Additional information is included for specific variables to help general users better understand the concepts and questions used in the census.

Release date: 2022-11-30
68. Languages Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021003
Description:
This reference guide provides information to help users effectively use and interpret language data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Release date: 2022-11-30
69. Commuting Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021011
Description: This reference guide provides information to help users effectively use and interpret commuting data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-11-30
70. Labour Reference Guide, Census of Population, 2021
Surveys and statistical programs – Documentation: 98-500-X2021012
Description: This reference guide provides information to help users effectively use and interpret labour data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.
Release date: 2022-11-30

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Date modified:: 2024-06-29

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