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- Census of Population (264)
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Results
All (1,889)
All (1,889) (10 to 20 of 1,889 results)
- Stats in brief: 11-001-X202423423765Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-21
- Stats in brief: 11-001-X20242343556Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-21
- Journals and periodicals: 62F0014MGeography: CanadaDescription: 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: 2024-08-20
- Stats in brief: 11-001-X20242333665Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-20
- Articles and reports: 62F0014M2024005Description: As part of its modernization initiative, Statistics Canada has been working with major Canadian wireless services providers (WSPs) to obtain transaction data for wireless plans. This document details the methodology used to incorporate transaction data in the cellular services price index (CSPI). The result is a “hybrid” index that combines the transaction data from participating WSPs with web collected data from the remaining WSPs in the sample.Release date: 2024-08-20
- Stats in brief: 11-001-X202423219277Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-19
- Stats in brief: 11-001-X202423237307Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-19
- Stats in brief: 11-001-X20242293496Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-16
- Stats in brief: 11-001-X20242293628Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-16
- Articles and reports: 37-20-00012024002Description: This technical reference guide (updated to include the 2024 datasets) is intended for users of the Education and Labour Market Longitudinal Platform (ELMLP). The data for the products associated with this issue are derived from integrating Postsecondary Student Information System (PSIS) administrative data with other administrative data on earnings. Statistics Canada has derived a series of annual indicators on the labour market outcomes of public postsecondary graduates including median employment income by educational qualification, field of study, age group and gender for Canada, the provinces and the territories combined.Release date: 2024-08-15
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Stats in brief (563)
Stats in brief (563) (0 to 10 of 563 results)
- Stats in brief: 11-001-X202423624744Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-23
- Stats in brief: 11-001-X20242363660Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-23
- Stats in brief: 11-001-X20242363682Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-23
- Stats in brief: 11-001-X20242353537Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-22
- Stats in brief: 11-001-X202423538749Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-22
- Stats in brief: 11-001-X202423423765Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-21
- Stats in brief: 11-001-X20242343556Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-21
- Stats in brief: 11-001-X20242333665Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-20
- Stats in brief: 11-001-X202423219277Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-19
- Stats in brief: 11-001-X202423237307Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-08-19
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Articles and reports (1,192)
Articles and reports (1,192) (30 to 40 of 1,192 results)
- Articles and reports: 12-001-X202400100001Description: 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
- Articles and reports: 12-001-X202400100002Description: 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
- Articles and reports: 12-001-X202400100003Description: 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
- Articles and reports: 12-001-X202400100004Description: 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-X202400100005Description: 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-X202400100006Description: 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-X202400100007Description: 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-X202400100008Description: 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-X202400100009Description: 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-X202400100010Description: 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
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Journals and periodicals (134)
Journals and periodicals (134) (0 to 10 of 134 results)
- Journals and periodicals: 11-621-MGeography: CanadaDescription: 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: 2024-08-22
- Journals and periodicals: 82-003-XGeography: CanadaDescription:
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: 2024-08-21 - Journals and periodicals: 62F0014MGeography: CanadaDescription: 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: 2024-08-20
- Journals and periodicals: 45-20-0003Description: The ‘Eh Sayers’ podcast explores data of interest to Canadians, like social or news-worthy topics. It also aims to foster data literacy and deliver insight into the lives of Canadians by exploring the data the agency produces and tying it to real life situations through storytelling.Release date: 2024-08-14
- Journals and periodicals: 89-653-XDescription: The Indigenous Peoples Survey (IPS) is a national survey on the social and economic conditions of First Nations people living off reserve, Métis and Inuit. The objectives of the IPS are to identify the needs of these Indigenous groups and to inform policy and programming activities aimed at improving the well-being of Indigenous peoples. The IPS aims to provide current and relevant data for a variety of stakeholders, including Indigenous organizations, communities, service providers, researchers, governments and the general public. The 2017 APS represents the fifth cycle of the survey and focuses on participation in the Canadian economy, transferable skills, practical training, use of information technology and Indigenous language attainment of First Nations people living off reserve, Métis and Inuit aged 15 years and over. The 2022 IPS represents the sixth cycle of the survey and focuses on families and children including child care, access to services, family stability, intergenerational trauma and discrimination, sense of belonging, and Indigenous languages and culture, of First Nations people living off reserve, Métis and Inuit aged 1 year and over.Release date: 2024-08-14
- Journals and periodicals: 89-657-XDescription: This thematic series groups different statistical products related to ethnicity, languages, and immigration. It features analytical documents of varying scopes, such as population profiles, reference materials, data products (including tables and factsheets), among other document types.Release date: 2024-08-07
- Journals and periodicals: 75-006-XGeography: CanadaDescription: This publication brings together and analyzes a wide range of data sources in order to provide information on various aspects of Canadian society, including labour, income, education, social, and demographic issues, that affect the lives of Canadians.Release date: 2024-08-06
- Journals and periodicals: 11-627-MDescription: 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: 2024-07-30 - Journals and periodicals: 14-28-0001Description: 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
- Journals and periodicals: 11-631-XDescription: Statistics Canada regularly prepares presentations with statistical findings about the country’s economy, society and environment. These presentations may be intended for conferences, meetings with stakeholders, or other events held throughout the year to provide Statistics Canada with an opportunity to promote the role of official statistics and to better understand data users’ needs. This series provides online access to these presentations as well as new presentations created to help communicate research findings on a wide range of subjects to a broad audience.Release date: 2024-07-24
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