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Description:

This discussion attempts to add to Wu’s review of inference from non-probability samples, as well as to highlighting aspects that are likely avenues for useful additional work. It concludes with a call for an organized stable of high-quality probability surveys that will be focused on providing adjustment information for non-probability surveys.

Description:

Strong assumptions are required to make inferences about a finite population from a nonprobability sample. Statistics from a nonprobability sample should be accompanied by evidence that the assumptions are met and that point estimates and confidence intervals are fit for use. I describe some diagnostics that can be used to assess the model assumptions, and discuss issues to consider when deciding whether to use data from a nonprobability sample.

Description:

Non-probability samples are deprived of the powerful design probability for randomization-based inference. This deprivation, however, encourages us to take advantage of a natural divine probability that comes with any finite population. A key metric from this perspective is the data defect correlation (ddc), which is the model-free finite-population correlation between the individual’s sample inclusion indicator and the individual’s attribute being sampled. A data generating mechanism is equivalent to a probability sampling, in terms of design effect, if and only if its corresponding ddc is of N-1/2 (stochastic) order, where N is the population size (Meng, 2018). Consequently, existing valid linear estimation methods for non-probability samples can be recast as various strategies to miniaturize the ddc down to the N-1/2 order. The quasi design-based methods accomplish this task by diminishing the variability among the N inclusion propensities via weighting. The super-population model-based approach achieves the same goal through reducing the variability of the N individual attributes by replacing them with their residuals from a regression model. The doubly robust estimators enjoy their celebrated property because a correlation is zero whenever one of the variables being correlated is constant, regardless of which one. Understanding the commonality of these methods through ddc also helps us see clearly the possibility of “double-plus robustness”: a valid estimation without relying on the full validity of either the regression model or the estimated inclusion propensity, neither of which is guaranteed because both rely on device probability. The insight generated by ddc also suggests counterbalancing sub-sampling, a strategy aimed at creating a miniature of the population out of a non-probability sample, and with favorable quality-quantity trade-off because mean-squared errors are much more sensitive to ddc than to the sample size, especially for large populations.

Description:

Statistical inference with non-probability survey samples is a notoriously challenging problem in statistics. We introduce two new methods of nonparametric propensity score technique for weighting in the non-probability samples. One is the information projection approach and the other is the uniform calibration in the reproducing kernel Hilbert space.

Description:

This response contains additional remarks on a few selected issues raised by the discussants.

Description:

Multiple imputation (MI) is a popular approach for dealing with missing data arising from non-response in sample surveys. Multiple imputation by chained equations (MICE) is one of the most widely used MI algorithms for multivariate data, but it lacks theoretical foundation and is computationally intensive. Recently, missing data imputation methods based on deep learning models have been developed with encouraging results in small studies. However, there has been limited research on evaluating their performance in realistic settings compared to MICE, particularly in big surveys. We conduct extensive simulation studies based on a subsample of the American Community Survey to compare the repeated sampling properties of four machine learning based MI methods: MICE with classification trees, MICE with random forests, generative adversarial imputation networks, and multiple imputation using denoising autoencoders. We find the deep learning imputation methods are superior to MICE in terms of computational time. However, with the default choice of hyperparameters in the common software packages, MICE with classification trees consistently outperforms, often by a large margin, the deep learning imputation methods in terms of bias, mean squared error, and coverage under a range of realistic settings.

Description:

Multilevel time series (MTS) models are applied to estimate trends in time series of antenatal care coverage at several administrative levels in Bangladesh, based on repeated editions of the Bangladesh Demographic and Health Survey (BDHS) within the period 1994-2014. MTS models are expressed in an hierarchical Bayesian framework and fitted using Markov Chain Monte Carlo simulations. The models account for varying time lags of three or four years between the editions of the BDHS and provide predictions for the intervening years as well. It is proposed to apply cross-sectional Fay-Herriot models to the survey years separately at district level, which is the most detailed regional level. Time series of these small domain predictions at the district level and their variance-covariance matrices are used as input series for the MTS models. Spatial correlations among districts, random intercept and slope at the district level, and different trend models at district level and higher regional levels are examined in the MTS models to borrow strength over time and space. Trend estimates at district level are obtained directly from the model outputs, while trend estimates at higher regional and national levels are obtained by aggregation of the district level predictions, resulting in a numerically consistent set of trend estimates.

Description:

Two-phase sampling is a cost effective sampling design employed extensively in surveys. In this paper a method of most efficient linear estimation of totals in two-phase sampling is proposed, which exploits optimally auxiliary survey information. First, a best linear unbiased estimator (BLUE) of any total is formally derived in analytic form, and shown to be also a calibration estimator. Then, a proper reformulation of such a BLUE and estimation of its unknown coefficients leads to the construction of an “optimal” regression estimator, which can also be obtained through a suitable calibration procedure. A distinctive feature of such calibration is the alignment of estimates from the two phases in an one-step procedure involving the combined first-and-second phase samples. Optimal estimation is feasible for certain two-phase designs that are used often in large scale surveys. For general two-phase designs, an alternative calibration procedure gives a generalized regression estimator as an approximate optimal estimator. The proposed general approach to optimal estimation leads to the most effective use of the available auxiliary information in any two-phase survey. The advantages of this approach over existing methods of estimation in two-phase sampling are shown both theoretically and through a simulation study.

Description:

In many applications, the population means of geographically adjacent small areas exhibit a spatial variation. If available auxiliary variables do not adequately account for the spatial pattern, the residual variation will be included in the random effects. As a result, the independent and identical distribution assumption on random effects of the Fay-Herriot model will fail. Furthermore, limited resources often prevent numerous sub-populations from being included in the sample, resulting in non-sampled small areas. The problem can be exacerbated for predicting means of non-sampled small areas using the above Fay-Herriot model as the predictions will be made based solely on the auxiliary variables. To address such inadequacy, we consider Bayesian spatial random-effect models that can accommodate multiple non-sampled areas. Under mild conditions, we establish the propriety of the posterior distributions for various spatial models for a useful class of improper prior densities on model parameters. The effectiveness of these spatial models is assessed based on simulated and real data. Specifically, we examine predictions of statewide four-person family median incomes based on the 1990 Current Population Survey and the 1980 Census for the United States of America.

Description:

A variety of different factors impact the ability of Canadian businesses to operate, such as the geographical location of businesses, the industry the businesses operate in, and the size of businesses. Differences may also be apparent when looking at different categories of business owners, as different segments of the Canadian population face different challenges at a personal level, and as owners of businesses. From the beginning of October to early November 2022, Statistics Canada conducted the Canadian Survey on Business Conditions (CSBC) to collect information on the environment businesses are currently operating in and their expectations moving forward. This article explores results from the survey by looking at the businesses majority-owned by immigrants to Canada and businesses majority-owned by racialized persons. While there is some degree of crossover between these two sub-populations, they are two distinct groups and face different challenges. The information and trends presented in this article are based on data collected via the CSBC.

Description: These static thematic maps provide the spatial density distribution of specific Census of Agriculture data themes by census division (CD). The data portrayed in these maps may be qualitative (e.g., predominant farm types) or quantitative (e.g., livestock inventory variation between the last two censuses).

This product is provided in printable format.

Description: These static thematic maps provide the spatial density distribution of specific Census of Agriculture data themes by census division (CD). The data portrayed in these maps may be qualitative (e.g., predominant farm types) or quantitative (e.g., livestock inventory variation between the last two censuses).

This product is provided in printable format.

Description: The Census of Agriculture Mapping Tool is a user-friendly interactive web mapping application that allows for a quick visualization of the spatial distribution of Census of Agriculture data, for any census year since 2016. Users can select census variables for viewing at four geographic levels: province or territory, census agricultural region (CAR), census division (CD) and census consolidated subdivision (CCS).

Notes: A reference guide for this product is available from within the tool (follow the link below).

Description: This profile presents information from the 2021 Census of Population for various levels of geography, including provinces and territories, census metropolitan areas, communities and census tracts. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description:

This product presents information from the Census of Population for various levels of geography. Data are from the 2021 Census of Population and are available according to the major releases of the 2021 Census release dates: February 9, 2022 – Population and dwelling counts; April 27, 2022 – Age, Sex at birth and gender, Type of dwelling; July 13, 2022 – Families, households and marital status, Canadian military experience, Income; August 17, 2022 – Language; September 21, 2022 – Indigenous peoples, Housing; October 26, 2022 – Immigration, place of birth, and citizenship, Ethnocultural and religious diversity, Mobility and migration; November 30, 2022 – Education, Labour, Language of work, Commuting, Instruction in the official minority language. Starting with the population and dwelling counts release and on major days of release thereafter, profile component data are available at the following geographic levels: Canada, province and territory, economic region, census division, census subdivision, census metropolitan area, census agglomeration, population centre, census tract, designated place, federal electoral district, aggregate dissemination area and dissemination area. This product may be downloaded in various formats, which include CSV, TAB or IVT.

Description: The COVID-19 lockdowns early in the pandemic had significant impacts on employment in both Canada and the United States. Post-COVID-19, the labour markets have behaved quite differently in their recovery phases. While there have been some similarities, especially by industry, there have been some stark differences as well. This paper examines the differences between the two labour markets post-lockdown by comparing the employment recovery of the various industries, the labour force participation rates, and labour churn.

Description: Most PhD (Doctor of Philosophy) graduates from Canadian universities work outside academia, but little is known about the nature of these jobs. This study examines the types of jobs held by doctoral graduates who worked outside academia. In addition to examining occupations, the study focuses on analyzing the task content of those jobs.

Description: Immigrant integration is a multidimensional concept that spans economic, social and political contexts, and should include the psychological well-being of its subject. This study compares the perceptions held by immigrants and Canadian-born people of shared democratic values—such as human rights, gender equality, and ethnic and cultural diversity—in Canadian society.

Description: In recent years, Statistics Canada has released data and analysis on business ownership by women and persons with disabilities. Furthermore, in an effort to continue to fill the information gap on business ownership by employment equity groups and better inform policy making, Statistics Canada has released, for the first time, time series on Indigenous-owned businesses by sex of ownership and other characteristics such as age of primary owner and province of operation.

Description:

Businesses are aiming to retain employees in order to keep up with increased supply and demand pressures. Based on the results of the Canadian Survey on Business Conditions, most businesses were likely to expect obstacles regarding the retention of current staff as well as the recruitment of new staff in order to fill vacant positions they may be experiencing. Almost half of businesses foresee rising costs of inputs and labour to be an obstacle in addressing staffing challenges. This article provides insights on the topics of challenges of hiring and vacant positions.

Description:

The 2021 Census of Agriculture collected data on Canadian potatoes. This infographic highlights a part of the potato value chain by using data from various sources.

Description:

The prevalence of diabetes mellitus in adults is increasing in Canada and worldwide, due to population aging as well as various social, environmental, and genetic factors. The objective of this study was to examine different individual and neighbourhood characteristics and their independent associations with risk of hospitalization for diabetes (type 1 or type 2) and selected commonly comorbid conditions among the high-risk Canadian adult population.

Description:

Strong, positive relationships are critical to the healthy development of adolescents in their transition to adulthood. Using 2017/2018 reports from the nationally representative Health Behaviour in School-aged Children study, this study examined the strength, consistency and significance of associations between “intensive” social media use (frequent use to connect with other people) and “problematic” social media use (use that depicts addictive qualities) and available measures of adolescent relationships and connections.

Description:

Eye health is an indicator of health in general, and of quality of life in particular. The objective of this study using cycles 5 and 6 of the Canadian Health Measures Survey (CHMS) was to determine which endogenous and sociodemographic factors were associated with visiting an eye care specialist in the previous year.

Description:

Canada’s COVID-19 vaccination campaign began on December 14, 2020 with the arrival of a limited number of doses which were prioritized for high-risk populations, such as the elderly, residents and staff of congregate living settings, frontline healthcare workers, and Indigenous populations. Using data from the COVID-19 Vaccination Coverage Survey (CVCS), this study’s objective was to examine sociodemographic disparities in COVID-19 vaccination uptake and intent by identifying the social and economic determinants associated with vaccination uptake among seniors aged 60 years and older (i.e., those eligible for vaccination at the time of the survey) and the determinants of vaccination intent in the entire adult population.

Description: This reference guide provides information to help users effectively use and interpret income data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This video will explain the concept of minority official language. It provides information on the new census questions regarding instruction in the minority official language, eligibility for education in minority official language and the usefulness of data on language of instruction for planning purposes.

Description: This reference guide provides information to help users effectively use and interpret education data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: The Census Dictionary is a reference document which contains detailed definitions of Census of Population concepts, variables and geographic terms, as well as historical information.

By referring to the Census Dictionary, both beginner and intermediate data users will gain a better understanding of the data and how to compare variables between census years.

The Census Dictionary will be released iteratively starting with geography and non-data dependent topic definitions, tables, figures and appendices with additional content made available based on subsequent topic releases.

Description:

The Guide to the Census of Population is a reference document that describes the various phases of the 2021 Census of Population. The guide provides an overview of content determination, sampling design, collection, data processing, data quality assessment, confidentiality guidelines and dissemination. It also includes response rates and other data quality information. This product may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2021 Census of Population.

The Guide to the Census of Population combines information previously available in the Overview of the Census, National Household Survey User Guide and the Data Quality and Confidentiality Standards and Guidelines from 2011. 

Description: The Guide to the Census of Population is a reference document that describes the various phases of the 2021 Census of Population. The guide provides an overview of content determination, sampling design, collection, data processing, data quality assessment, confidentiality guidelines and dissemination. It also includes response rates and other data quality information. This product may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2021 Census of Population.

Description:

This guide focuses on the following topic: education. This reference guide provides information that enables users to effectively use, apply and interpret data from the 2016 Census. This guide contains definitions and explanations of concepts, classifications, data quality and comparability to other sources. Additional information is included for specific variables to help general users better understand the concepts and questions used in the census.

Description:

This reference guide provides information to help users effectively use and interpret language data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret commuting data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.

Description: This reference guide provides information to help users effectively use and interpret labour data from the 2021 Census. This guide contains definitions and explanations of concepts, questions, classifications, data quality and comparability with other sources for this topic.