Analysis

Description: Release published in The Daily – Statistics Canada’s official release bulletin

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.

Description: We provide comparisons among three parametric methods for the estimation of participation probabilities and some brief comments on homogeneous groups and post-stratification.

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.

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.

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.

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.

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.

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.

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.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Using the Employment Insurance Coverage Survey, this paper studies the share of spouses or partners of biological or adoptive mothers who claimed or intended to claim parental benefits from 2006 to 2022.

Description: This paper looks at how extreme weather claims have impacted the insurance industry in Canada from 2020 to 2023. A specific focus is given to homeowners insurance, which during this time, homeowners insurance consumer price index exceeded all items inflation. Insurer profitability and consumer impacts are analyzed given the significant uptick in catastrophic claims. All four years analyzed ranked in the top 10 most costly claims years in Canadian history, costing billions each year. In addition, other contributing factors are explored to provide a robust overview of trends in profitability of the insurance industry.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: This infographic focuses on innovation and business strategy in Canada, based on data from the 2022 Survey of Innovation and Business Strategy. It presents the long-term strategy for innovative businesses and non-innovative businesses, the innovation rate and intellectual property(IP) ownership for multinational businesses and non-multinational businesses, the competition, and the skill shortages in Canadian businesses.

Description: Release published in The Daily – Statistics Canada’s official release bulletin

Description: Are you feeling like it's a little bit harder to bring home the bacon... from the grocery store? The latest data indicate that food prices have mostly stabilized... but why does it feel like the cost of feeding your family is still going up? Today, we're talking food inflation with StatCan's resident smart cookie Taylor Mitchell.

Description:

Why do innovation surveys produce radically different estimates of the number of R&D performers than R&D surveys? The factors contributing to divergence are presented with detail on selected contributors.

Description:

Given the high cost of R&D, adopting the correct strategies and mix of products is required for success for Canadian biotechnology firms. A recent survey examined the rapid growth of 30 companies. Fast-growing enterprises adopted a strategy of patenting their products, avoiding major production delays, targeting export markets, accessing venture capital, conducting key alliances, and planning the IPO.

Description:

Technological change and innovations depend greatly on R&D activities and investments. R&D is concentrated around the "core firms" that are responsible for 87% of expenditures. Biotechnology R&D performers accounted for $904 million of R&D expenditure. Biotechnology R&D is concentrated in large firms with 75% of R&D occuring in firms with 100 or more employees. Almost 77% of funding sources for R&D in biotechnology came from the private sector and 21% from foreign sources.

Description:

In the private sector, 10.1% of enterprises use the Internet to sell goods and services. The information and cultural industries utilize this growing form of commerce the greatest (20.1%). In comparison, 14.5% of public sector institutions sell goods or services with educational services leading the way, followed by federal and provincial governments.

Description:

Location, location, location - is it important in research and technology? Statistics Canada survey data are being used to provide a new approach to analyze the usefulness of mapping key innovation indicators. By attaching survey data sets to sources with a larger sample size, detailed geographic distributions of establishments are estimated. Numerous data sets are being explored with the benefits to be realized in an interactive GIS.

Description:

This paper discusses methods and tools considered and used to produce cross-sectional estimates based on the combination of two longitudinal panels for the Survey of Labour and Income Dynamics (SLID).

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This paper provides data from several household surveys to document how pension coverage of young and prime-aged workers has evolved in Canada between the mid-1980s and the mid-1990s.

Description:

This Juristat presents and analyzes information on young offender admissions to custody and community services, with breakdowns by custody (secure custody, open custody, remand) and probation, and key case characteristics such as age, sex, Aboriginal/non-Aboriginal status, and most serious offence. In addition, it includes data pertaining to releases from remand, secure custody, and open custody by sex and time served. These breakdowns are presented and analyzed at the national and provincial/territorial level.

Data summarized in this Juristat are primarily drawn from the national Youth Custody and Community Services (YCCS) Survey. The scope of the survey is to collect and analyze information on the application of dispositions under the Young Offenders Act from provincial and territorial agencies responsible for youth corrections and programs.

Description:

Farm operators and farm families in Canada are a diverse group. Farm operators differ by age, experience, business expectations, size and scale. These differences account for the varying responses these farmers have to farm programs and other government policies. To determine these responses, a farm "typology" has been developed to take account of the factors influencing their behavior.

Description:

This article looks at the changes in immigration to Canada during the 20th century.

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.

Description:

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

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.

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.

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.

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.

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.

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.

Description: This series of analytical articles provides insights on the socio-economic environment in rural communities in Canada. New articles will be released periodically.

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.