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

  • 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

  • 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
Stats in brief (2,664)

Stats in brief (2,664) (40 to 50 of 2,664 results)

Articles and reports (7,005)

Articles and reports (7,005) (5,820 to 5,830 of 7,005 results)

  • Articles and reports: 88-003-X19990025340
    Geography: Canada
    Description:

    In 1999, the federal government expects to fund 19.4% of the R&D in Canada. Less and less of the government-funded R&D is taking place in government labs. Although overall spending on R&D will increase from $3.5 billion to $4.0 billion, the share of this going to the government research has dropped from 59% to 52%.

    Release date: 2000-01-17

  • Articles and reports: 88-003-X19990025341
    Geography: Canada
    Description:

    You thought it was obvious but the ICT sector that everyone is talking about hasn't had an official definition - until now. We sorted through the SIC (1980) codes and selected 20 that fit. Next issue - the NAICS-based definitions.

    Release date: 2000-01-17

  • Articles and reports: 88-003-X19990025342
    Geography: Canada
    Description:

    Our jobs, communities, leisure activities and patterns of commerce are changing at a dizzying pace - the Internet is literally transforming the way we live, work and play. In 1998, 36% of Canadian households were regular users of computer communication - up sharply from 29% in 1997. And the technology revolution is not over yet!

    Release date: 2000-01-17

  • Articles and reports: 88-003-X19990025343
    Geography: Canada
    Description:

    Gross domestic product expenditures on R&D (GERD) for 1999 increased by 3.5% to $14.9 billion over the previous year. Despite this increase, the proportion of GDP devoted to R&D (1.6%) is still among the lowest of the G-7 countries.

    Release date: 2000-01-17

  • Articles and reports: 88-003-X19990025344
    Geography: Canada
    Description:

    A Statistics Canada study uses business demographics to learn about innovation and technological change and uncovers interesting patterns. Contrary to expectations, the author uncovered considerable volatility (start-ups and closures) in the service sector. The volatility rate for this sector was 31% compared with 23% for the manufacturing sector. Firms that do not innovate frequently are replaced by new ones that have new or improved products to offer or by those that employ more efficient methods of production and delivery.

    Release date: 2000-01-17

  • Articles and reports: 88-003-X19990025345
    Geography: Canada
    Description:

    Some analysts suggest that biotechnology may trigger a revolution equal to the one prompted by information technology. Various sectors of Canadian industry are already actively using biotechnologies for purposes ranging from research and development to pollution control. Many still see obstacles to adopting new biotechnologies including lack of information and government regulation.

    Release date: 2000-01-17

  • Articles and reports: 87-003-X20000014858
    Geography: Canada
    Description:

    In the first part of this study, we will explore the development of the ski industry in Canada, after taking a short historical detour. In part two we will examine the characteristics of American travellers who visited Canadian ski areas (to ski or snowboard) during an overnight stay in Canada in the winter of 1998-99. Lastly, we will take a quick look at some characteristics of the overseas skier/snowboarder and at their contribution to the Canadian economy.

    Release date: 2000-01-14

  • Articles and reports: 21-601-M1996030
    Description:

    This paper looks at trends in rural employment in Canada and compares them with trends for other Organisation for Economic Co-operation and Development (OECD) countries.

    Release date: 2000-01-14

  • Articles and reports: 21-601-M1996031
    Description:

    This paper looks at non-metropolitan areas in Canada in depth by breaking them down into three smaller areas using the Metropolitan Influence Zones (MIZ) conceptual framework. It then looks at the differences between these areas.

    Release date: 2000-01-14

  • Articles and reports: 21-601-M1998033
    Description:

    This paper examines hobby farming in Canada and the factors that keep hobby farmers farming.

    Release date: 2000-01-14
Journals and periodicals (323)

Journals and periodicals (323) (0 to 10 of 323 results)

  • Journals and periodicals: 11-522-X
    Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
    Release date: 2024-06-28

  • Journals and periodicals: 75-005-M
    Description: The papers in this series cover a variety of technical topics related to the Centre for Labour Market Information programs, such as the Labour Force Survey, the Survey of Employment Payrolls and Hours, the Employment insurance Coverage Survey, the Employment Insurance Statistics program as well as data from administrative sources.
    Release date: 2024-06-27

  • Journals and periodicals: 36-28-0001
    Description: Economic and Social Reports includes in-depth research, brief analyses, and current economic updates on a variety of topics, such as labour, immigration, education and skills, income mobility, well-being, aging, firm dynamics, productivity, economic transitions, and economic geography. All the papers are institutionally reviewed and the research and analytical papers undergo peer review to ensure that they conform to Statistics Canada's mandate as a governmental statistical agency and adhere to generally accepted standards of good professional practice.
    Release date: 2024-06-26

  • Journals and periodicals: 11-627-M
    Description: Every year, Statistics Canada collects data from hundreds of surveys. As the amount of data gathered increases, Statistics Canada has introduced infographics to help people, business owners, academics, and management at all levels, understand key information derived from the data. Infographics can be used to quickly communicate a message, to simplify the presentation of large amounts of data, to see data patterns and relationships, and to monitor changes in variables over time.

    These infographics will provide a quick overview of Statistics Canada survey data.

    Release date: 2024-06-25

  • Journals and periodicals: 12-001-X
    Geography: Canada
    Description: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.
    Release date: 2024-06-25

  • Table: 91-520-X
    Description: This report presents the results of the population projections by age group and sex for Canada, the provinces and territories. These projections are based on assumptions that take into account the most recent trends relating to components of population growth, particularly fertility, mortality, immigration, emigration and interprovincial migration.

    The detailed data tables are available in CODR: tables 1710005701 and 1710005801.

    Release date: 2024-06-24

  • 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

  • Journals and periodicals: 82-003-X
    Geography: Canada
    Description:

    Health Reports, published by the Health Analysis Division of Statistics Canada, is a peer-reviewed journal of population health and health services research. It is designed for a broad audience that includes health professionals, researchers, policymakers, and the general public. The journal publishes articles of wide interest that contain original and timely analyses of national or provincial/territorial surveys or administrative databases. New articles are published electronically each month.

    Health Reports had an impact factor of 5.0 for 2022 and a five-year impact factor of 5.6. All articles are indexed in PubMed. Our online catalogue is free and receives more than 700,000 visits per year. External submissions are welcome.
    Release date: 2024-06-19

  • Journals and periodicals: 62F0014M
    Geography: Canada
    Description: The Prices Analytical Series provides research and analysis pertaining to price indices. The Analytical series is intended to stimulate discussion on a variety of topics related to the analysis of the evolution of prices through time or space.
    Release date: 2024-06-18

  • Journals and periodicals: 71-222-X
    Description: Labour Statistics at a Glance features short analytical articles on specific topics of interest related to Canada's labour market. The studies examine recent or historical trends using data produced by the Centre for Labour Market Information, i.e., the Labour Force Survey, the Survey of Employment Payrolls and Hours, the Job Vacancy and Wage Survey, the Employment Insurance Coverage Survey and the Employment Insurance Statistics Program.
    Release date: 2024-06-13
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