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All (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
Stats in brief (2,664)

Stats in brief (2,664) (50 to 60 of 2,664 results)

Articles and reports (7,003)

Articles and reports (7,003) (40 to 50 of 7,003 results)

  • 41. High Inflation in 2022 in Canada: Demand–pull or supply–push?
    Articles and reports: 36-28-0001202400500005
    Description: Headline inflation in Canada reached a 40-year high in 2022. Rising prices reduced the purchasing power of people whose incomes were not keeping pace with inflation and the current high inflation in Canada, as well as in many other countries, may be caused by both demand and supply factors. This article examines whether the current high inflation in Canada is demand–pull or supply–push.
    Release date: 2024-05-22
  • 42. Survival and growth of women-owned and immigrant-owned businesses during the COVID-19 pandemic
    Articles and reports: 36-28-0001202400500006
    Description: The pandemic has had an unprecedented impact on the Canadian economy. This impact was uneven across different workers and businesses. However, there is little information available on how businesses were affected by and survived through the pandemic according to the characteristics of their owners, especially those owned by certain groups such as women and immigrants. This article uses a linkage of the monthly business openings and closures with the Canadian Employer-Employee Dynamics Database and the Canada Emergency Wage Subsidy to study the survival rate and employment growth of businesses by gender, and immigrant status of owners.
    Release date: 2024-05-22
  • 43. Innovation in focus: Exploring trends in the development of advanced technology through patent applications
    Articles and reports: 22-20-00012024002
    Description: This article explores trends in patent applications made by Canadian-resident businesses for advanced technologies from 2001 to 2019, drawing on Eurostat's aggregation of high-tech patents. Approximately one-third of applications fall under high-tech categories, the bulk of which were associated with Communication, Computer, and Automated business equipment technologies. While these fields saw growth until 2012, a subsequent decline occurred, notably in Computer and Electronic Product Manufacturing. Biotechnology, Semiconductors, and Lasers showed limited dynamism, while aviation technology applications surged by nearly twentyfold over the period.
    Release date: 2024-05-21
  • 44. From Shelf to Statistic: An Overview of Food Price Measurement in the Consumer Price Index
    Articles and reports: 62F0014M2024003
    Description: This technical paper describes the collection of food price data and the methodologies that are used to provide Canadians with accurate and timely food inflation data in both the CPI and the monthly average retail prices table.
    Release date: 2024-05-21
  • 45. Digital Insights
    Articles and reports: 22-20-0001
    Description: Digital Insights brings together a variety of data from across Statistics Canada and other sources to provide insights and analysis on the digital economy and society in Canada. The topics covered include: e-commerce, digital trade, cyber security and cybercrime, and the impacts of Internet and other technology use on the Canadian economy and society.
    Release date: 2024-05-21
  • 46. Direct and Indirect Support for Innovation in Canada
    Articles and reports: 18-001-X2024003
    Description: This study compares the Government of Canada’s direct and indirect measures to support R&D, as captured by business innovation and growth support (BIGS) programs and the Scientific Research and Experimental Development (SR&ED) tax incentive program. BIGS and SR&ED are two central instruments that the Canadian government uses to stimulate R&D expenditures in the business sector.
    Release date: 2024-05-17
  • 47. Sociodemographic differences in recreational screen time before and during the COVID-19 pandemic in Canada
    Articles and reports: 82-003-X202400500001
    Description: Over the last several years, recreational screen time has been increasing. During the COVID-19 pandemic, recreational screen time rose among Canadian youth and adults, and those who increased screen time had poorer self-reported mental health. Using data from the 2017, 2018, and 2021 Canadian Community Health Survey, the objective of this study was to compare recreational screen time behaviours before (2018) and during (2021) the pandemic, looking at patterns by sociodemographic subgroups of the Canadian population.
    Release date: 2024-05-15
  • 48. Harmonizing the assessment of allostatic load across cycles of the Canadian Health Measures Survey: Variable selection and calculation method
    Articles and reports: 82-003-X202400500002
    Description: The availability of measures to operationalize allostatic load—the cumulative toll on the body of responding to stressor demands—in population health surveys may differ across years or surveys, hampering analyses on the entire sampled population. In this study, the impacts of variable selection and calculation method were evaluated to generate an allostatic load index applicable across all cycles of the Canadian Health Measures Survey (CHMS). CHMS data were used to compare individual and population-level changes in scores for allostatic load indexes in which other commonly used measures were substituted for waist-to-hip ratio. Associations between the various constructs and indicators of socioeconomic position were then assessed to evaluate whether relationships were maintained across indexes.
    Release date: 2024-05-15
  • 49. Maps and key facts on schooling in English-language schools in Quebec, 2021
    Articles and reports: 89-657-X2024003
    Description: This series of regional maps shows the number of school-aged children eligible to primary and secondary instruction in English in Quebec by census subdivision, and the proportion of these children who attend or have attended an English-language school in Canada. All the information provided comes from the 2021 Census of Population and the 2022 Open Database of Educational Facilities.
    Release date: 2024-05-14
  • 50. New housing supply: Urban sprawl and densification
    Articles and reports: 46-28-0001202400100003
    Description: While many Canadians prefer to live in low-density housing, the supply of these units is linked to urban sprawl and attendant environmental and economic implications. This article examines recent trends of new housing supply and areas of urban sprawl in select Canadian cities. It also analyzes the characteristics of homeowners who live in neighbourhoods which have recently experienced urban sprawl.
    Release date: 2024-05-08
Journals and periodicals (323)

Journals and periodicals (323) (40 to 50 of 323 results)

  • 41. VISTA on the Agri-food Industry and the Farm Community
    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
  • 42. Report on Energy Supply and Demand in Canada: Explanatory Information
    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
  • 43. 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: 2023-11-15
  • 44. Statistics Canada: Departmental Sustainable Development Strategy, 2023 to 2027
    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
  • 45. Household Expenditures Research Paper Series
    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
  • 46. Statistical Methodology Research and Development Program Achievements
    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
  • 47. Environment Accounts and Statistics Analytical and Technical Paper Series
    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
  • 48. 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: 2023-07-28
  • 49. Rural and Small Town Canada Analysis Bulletin
    Journals and periodicals: 21-006-X
    Geography: Canada
    Description: This series of analytical articles provides insights on the socio-economic environment in rural communities in Canada. New articles will be released periodically.
    Release date: 2023-07-24
  • 50. Data Literacy Training Products
    Journals and periodicals: 89-20-0006
    Description: Statistics Canada is committed to sharing our knowledge and expertise to help all Canadians develop their data literacy skills by developing a series of data literacy training resources. Data literacy is a key skill needed in the 21st century. It is generally described as the ability to derive meaning from data. Data literacy focuses on the competencies or skills involved in working with data, including the ability to read, analyze, interpret, visualize data, as well as to drive good decision-making.
    Release date: 2023-07-17
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