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All (10,039) (60 to 70 of 10,039 results)

  • Stats in brief: 11-627-M2024032
    Description: This infographic is a visual representation of short-term rental (STR) activity across Canada, focusing particularly on the subset of STRs that could potentially be used for long-term housing. This subset of STRs is referred to as potential long-term dwellings (PLTDs), it comprises entire units listed for more than 180 days a year, excluding vacation-type properties.
    Release date: 2024-07-30

  • Stats in brief: 11-001-X202421218843
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-07-30

  • Articles and reports: 14-28-0001202400100001
    Description: In the publication Quality of Employment in Canada, the long working hours indicator is the number of employed persons who usually work 49 hours or more per week at their main and second job (if applicable), expressed as a percentage of all employed persons.
    Release date: 2024-07-25

  • Articles and reports: 14-28-0001202400100002
    Description: In the publication Quality of Employment in Canada, the multiple jobholder indicator is the number of employed persons who reported holding more than one job simultaneously during the reference week of the survey, expressed as a percentage of all employed persons.
    Release date: 2024-07-25

  • Articles and reports: 14-28-0001202400100003
    Description: In the publication Quality of Employment in Canada, the own-account worker rate indicator is the proportion of the employed population who are own-account workers. Own-account workers are defined as private-sector workers, who are self-employed and either unincorporated or incorporated without employees.
    Release date: 2024-07-25

  • Articles and reports: 14-28-0001202400100004
    Description: In the publication Quality of Employment in Canada, the employability indicator is the number of employees who feel it would be easy for them to find a job of a similar salary if they lost or quit their current job, expressed as a percentage of all employed persons.
    Release date: 2024-07-25

  • Stats in brief: 11-627-M2024030
    Description: Key statistics about crime in Canada are presented in this infographic. Findings on changes to the Crime Severity Index (CSI) at the national and provincial, territorial levels are presented. Also included are the categories of crime which were reported in 2023.
    Release date: 2024-07-25

  • Stats in brief: 11-001-X20242074751
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-07-25

  • Articles and reports: 22-20-00012024003
    Description: While the Internet has made it easier than ever to get information, it has also created new opportunities for misinformation to spread. Using 2023 data from the Survey Series on People and their Communities and 2022 data from the Canadian Internet Use Survey, this paper conducts multivariate analyses to examine the role of demographic and socioeconomic characteristics in the likelihood of engaging in particular fact-checking behaviours thought to be associated with the spread of misinformation.
    Release date: 2024-07-25

  • Journals and periodicals: 14-28-0001
    Description: Statistics Canada's Quality of Employment in Canada publication is intended to provide Canadians and Canadian organizations with a better understanding of quality of employment using an internationally-supported statistical framework. Quality of employment is approached as a multidimensional concept, characterized by different elements, which relate to human needs in various ways. To cover all relevant aspects, the framework identified seven dimensions and twelve sub-dimensions of quality of employment.
    Release date: 2024-07-25
Stats in brief (2,687)

Stats in brief (2,687) (40 to 50 of 2,687 results)

Articles and reports (7,030)

Articles and reports (7,030) (40 to 50 of 7,030 results)

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • 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

  • Articles and reports: 12-001-X202400100014
    Description: This paper is an introduction to the special issue on the use of nonprobability samples featuring three papers that were presented at the 29th Morris Hansen Lecture by Courtney Kennedy, Yan Li and Jean-François Beaumont.
    Release date: 2024-06-25
Journals and periodicals (322)

Journals and periodicals (322) (40 to 50 of 322 results)

  • Journals and periodicals: 91F0015M
    Geography: Canada
    Description: Demographic documentsis a series of texts intended for scholars and researchers, published occasionally by the Demography Division of Statistics Canada for their methodological, analytical or descriptive interest in the population field.
    Release date: 2024-02-02

  • Journals and periodicals: 11-633-X
    Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.
    Release date: 2024-01-22

  • Journals and periodicals: 85-603-X
    Description: This article presents results from the first Survey of Sexual Misconduct in the Canadian Armed Forces. Namely, the prevalence of general sexualized behaviour in the workplace; discrimination on the basis of sex, sexual orientation, or gender identity; personal experiences of discrimination or sexualized behaviour; the prevalence of sexual assault; and knowledge of policies on sexual misconduct and perceptions of responses to sexual misconduct are examined. Where possible, results are analyzed by sex, environmental command, type of service, age, rank, and number of years of service.
    Release date: 2023-12-05

  • Journals and periodicals: 85-005-X
    Geography: Canada
    Description: This publication features short, informative articles focusing on specific justice-related issues. For more in-depth articles on justice in Canada, see also Juristat, Catalogue no. 85-002-X.
    Release date: 2023-12-04

  • Journals and periodicals: 21-004-X
    Geography: Canada
    Description:

    Each issue contains a short article highlighting statistical insights on themes relating to agriculture, food and rural issues.

    Release date: 2023-11-30

  • Table: 57-003-X
    Description: This publication presents energy balance sheets in natural units and heat equivalents in primary and secondary forms, by province. Each balance sheet shows data on production, trade, interprovincial movements, conversion and consumption by sector. Analytical tables and details on non-energy products are also included. It includes explanatory notes, a historical energy summary table and data analysis. The publication also presents data on natural gas liquids, electricity generated from fossil fuels, solid wood waste and spent pulping liquor.
    Release date: 2023-11-20

  • Journals and periodicals: 45-26-0001
    Description: The Departmental Sustainable Development Strategy (DSDS) outlines departmental actions, with measurable performance indicators, that support the implementation strategies of the 2022-2026 Federal Sustainable Development Strategy. The DSDS further outlines Statistics Canada’s sustainable development vision to produce data to help track whether Canada is moving toward a more sustainable future and highlights projects with links to supporting sustainable development goals.
    Release date: 2023-11-14

  • Journals and periodicals: 62F0026M
    Description: This series provides detailed documentation on the issues, concepts, methodology, data quality and other relevant research related to household expenditures from the Survey of Household Spending, the Homeowner Repair and Renovation Survey and the Food Expenditure Survey.
    Release date: 2023-10-18

  • Journals and periodicals: 12-206-X
    Description: This report summarizes the annual achievements of the Methodology Research and Development Program (MRDP) sponsored by the Modern Statistical Methods and Data Science Branch at Statistics Canada. This program covers research and development activities in statistical methods with potentially broad application in the agency’s statistical programs; these activities would otherwise be less likely to be carried out during the provision of regular methodology services to those programs. The MRDP also includes activities that provide support in the application of past successful developments in order to promote the use of the results of research and development work. Selected prospective research activities are also presented.
    Release date: 2023-10-11

  • Journals and periodicals: 16-001-M
    Description: The series covers environment accounts and indicators, environmental surveys, spatial environmental information and other research related to environmental statistics. The technical paper series is intended to stimulate discussion on a range of environmental topics.
    Release date: 2023-09-13
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