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All (10,025) (70 to 80 of 10,025 results)

  • 71. Census of Population web pages: Introduction
    Stats in brief: 98-20-00032021031
    Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. This video will provide an overview of the major links and products on the main page that are available to all users.
    Release date: 2024-07-10
  • 72. Census of Population web pages: Profile Part 1, How to find and filter data
    Stats in brief: 98-20-00032021032
    Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. The purpose of this video is to explain where to find the most popular standard data product of the Census of Population, the 2021 Census Profile, and how to filter the data.
    Release date: 2024-07-10
  • 73. Census of Population web pages: Profile Part 2, Adding geographies and downloading options
    Stats in brief: 98-20-00032021033
    Description: This video is part of a series that is designed to give you a basic understanding of the Census of Population web pages. The purpose of this video is to explain how to add geographies in the 2021 Census Profile and to present the various downloading options to see the data.
    Release date: 2024-07-10
  • 74. Census of Population concept videos
    Journals and periodicals: 98-20-0003
    Description: Once every five years, the Census of Population provides a detailed and comprehensive statistical portrait of Canada that is vital to our country. It is the primary source of sociodemographic data for specific population groups such as lone-parent families, Indigenous peoples, immigrants, seniors and language groups.

    In order to help users of census products to better understand the various Census of Population concepts, Statistics Canada has developed, in the context of the activities of the 2021 Census and previous censuses, a collection of short videos. These videos are a reference source for users who are new to census concepts or those who have some experience with these concepts, but may need a refresher or would like to expand their knowledge.

    Release date: 2024-07-10
  • 75. Internal Trade in Canada: Value of interprovincial trade in manufactured goods 2022
    Stats in brief: 11-001-X202419138647
    Description: Release published in The Daily – Statistics Canada’s official release bulletin
    Release date: 2024-07-09
  • 76. A profile of 2SLGBTQ+ persons with disabilities, 2022
    Articles and reports: 89-654-X2024002
    Description: Using data from the 2022 Canadian Survey on Disability (CSD), this factsheet examines the experiences of 2SLGBTQ+ persons with disabilities. It provides information on various sociodemographic and disability characteristics, such as age, disability type, severity of disability, and employment. It also includes comparisons to the non-2SLGBTQ+ persons with disabilities population by age group.
    Release date: 2024-07-08
  • 77. Reports on Disability and Accessibility in Canada
    Journals and periodicals: 89-654-X
    Description: The Canadian Survey on Disability (CSD) is a national survey of Canadians aged 15 and over whose everyday activities are limited because of a long-term condition or health-related problem.
    Release date: 2024-07-08
  • 78. Airport Activity: Air Carrier Traffic at Canadian Airports, 2023
    Articles and reports: 51-004-X2024001
    Description: This report presents statistics on airline traffic such as the volume of passengers and cargo at Canadian airports.
    Release date: 2024-07-04
  • 79. Aviation
    Table: 51-004-X
    Description: This bulletin presents the most up-to-date available information extracted from all of the Aviation Statistics Centre's surveys. Regular features include releases on principal statistics for Canada's major air carriers, airport data, fare basis statistics and traffic data for Canada's most important markets.
    Release date: 2024-07-04
  • 80. Heterogeneous causal effects of labour market programs: A machine learning approach Archived
    Articles and reports: 11-522-X202200100017
    Description: In this paper, we look for presence of heterogeneity in conducting impact evaluations of the Skills Development intervention delivered under the Labour Market Development Agreements. We use linked longitudinal administrative data covering a sample of Skills Development participants from 2010 to 2017. We apply a causal machine-learning estimator as in Lechner (2019) to estimate the individualized program impacts at the finest aggregation level. These granular impacts reveal the distribution of net impacts facilitating further investigation as to what works for whom. The findings suggest statistically significant improvements in labour market outcomes for participants overall and for subgroups of policy interest.
    Release date: 2024-06-28
Stats in brief (2,682)

Stats in brief (2,682) (0 to 10 of 2,682 results)

Articles and reports (7,021)

Articles and reports (7,021) (30 to 40 of 7,021 results)

  • 31. 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
  • 32. 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
  • 33. 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
  • 34. 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
  • 35. 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
  • 36. 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
  • 37. 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
  • 38. 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
  • 39. 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
  • 40. 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
Journals and periodicals (322)

Journals and periodicals (322) (30 to 40 of 322 results)

  • 31. Income Research Paper Series
    Journals and periodicals: 75F0002M
    Description: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.
    Release date: 2024-04-26
  • 32. Juristat
    Journals and periodicals: 85-002-X
    Geography: Canada
    Description: This publication provides in-depth analysis and detailed statistics on a variety of topics and issues related to justice and public safety. Topics include crime, victimization, homicide, civil, family and criminal courts, and correctional services. Issues related to community safety, and perceptions of safety are also covered. The publication is intended for those with an interest in Canada's justice and public safety systems as well as those who plan, establish, administer and evaluate programs and projects related to justice and public safety.
    Release date: 2024-04-26
  • 33. Studies on Gender and Intersecting Identities
    Journals and periodicals: 45-20-0002
    Description: Studies on Gender and Intersecting Identities brings together and analyzes a wide range of important issues related to gender, age, sexuality, disability, ethnocultural characteristics and other intersecting identities. Through a Gender-based Analysis Plus (GBA+) lens, these studies will enrich Canadians' understanding of how gender and other identity factors affect the social, economic and financial participation and status of diverse groups of Canadians.
    Release date: 2024-03-25
  • 34. Canadian Agriculture at a Glance
    Journals and periodicals: 96-325-X
    Geography: Canada
    Description: This publication features short and accessible analytical articles that delve further into key findings and emerging trends identified in Census of Agriculture and other data sources related to agriculture. Subjects of analysis include matters related to farm land, crops, livestock, farm finances, technology, the environment and the farm population, as well as other economic and social aspects of Canada’s agriculture industry. Analytical articles are written in plain language and are intended to be a valuable source of information for a broad audience, including policy analysts, students, researchers, agricultural operators, the media and the public at large.
    Release date: 2024-03-07
  • 35. Labour Statistics: Research Papers
    Journals and periodicals: 75-004-M
    Geography: Canada
    Description: The papers in this series cover a variety of topics related to labour statistics. The studies are intended to show recent or historical trends observed with the surveys produced by the Centre for Labour Market Information, i.e. the Labour Force Survey, Survey of Employment Payrolls and Hours, Employment insurance Coverage Survey, Employment insurance statistics as well as administrative data sources. All the papers in this analytical series go through institutional and peer review to ensure that they conform to Statistics Canada's mandate as a government statistical agency and adhere to generally accepted standards of good professional practice.
    Release date: 2024-03-04
  • 36. Rural Statistics in Canada
    Journals and periodicals: 45-20-0004
    Description: The publication features products and data highlights that focus on rural areas of Canada or that have a rural dimension present. Rural areas are typically areas outside of Canada's Census Metropolitan Areas (CMA) and Census Agglomerations (CA). The publication also includes explanatory notes on key concepts and definitions.
    Release date: 2024-03-01
  • 37. Census in Brief
    Journals and periodicals: 98-200-X
    Description: These short analytical articles, based on data from the Census of Population, provide analysis on specific topics of interest related to the Canadian population. They are available with each Census of Population major release.
    Release date: 2024-02-28
  • 38. Annual Demographic Estimates: Canada, Provinces and Territories
    Journals and periodicals: 91-215-X
    Description: This publication presents annual estimates of the total population and annual estimates by age and gender for Canada, provinces and territories. It also presents estimates of the following components of population change: births, deaths, immigration, emigration, returning emigration, net non-permanent residents and inter-provincial migration, the latter by origin and destination. As in the case of population estimates, the components are also available for the total population and by age and gender.

    The Annual demographic estimates - Canada, provinces and territories publication contains the most recent estimates as well as an annual historical series. It also contains highlights and analysis of the most current demographic trends, as well as a brief description of the concepts, methods and data quality of the estimates.

    Release date: 2024-02-21
  • 39. Education, Learning and Training Research Paper Series
    Journals and periodicals: 81-595-M
    Geography: Canada
    Description: The series includes analysis on the characteristics of those with elementary-secondary, postsecondary and apprenticeship training. It also features analysis on students’ pathways through the education system and into the labour market-- including findings for different levels of education and fields of study. This research highlights specific groups of interest such as youth, women, men, immigrants, Indigenous people (First Nations people, Métis and Inuit) and visible minorities, and how intersections between these characteristics influence people’s educational experiences. Other topics include access to education; national and international adult performance assessments; use of technology; lifelong learning; and adult education.
    Release date: 2024-02-21
  • 40. Income and Expenditure Accounts Technical Series
    Journals and periodicals: 13-604-M
    Geography: Canada
    Description: These papers provide background information as well as in depth analysis on data reported in any of the following accounts: income and expenditure accounts, provincial economic accounts, financial flow accounts, national balance sheet accounts, estimates of labour income, and national tourism indicators.
    Release date: 2024-02-12
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