Analysis

Description:

In Canada, provincial and federal demographers have attempted to use various sets of administrative data to estimate migration flows. This paper presents the development of intra-provincial migration estimates using driver’s licence data in Ontario. An evaluation of these migration estimates has been carried out by comparing with those derived from the income tax data by Statistics Canada. Both files provide equally good and complimentary estimates of intra-provincial migration.

Description:

This paper examines the use of administrative files from Alberta’s Health Care Insurance Plans combined with Vital Statistics data as inputs for estimating population. Results, which are presented and compared with Census data, indicate that Health Care data can be used to produce accurate population estimates at the provincial level and for smaller areas such as census divisions and municipalities.

Description:

The accuracy of small area population estimates derived from a regression based model is heavily dependent on the ability of the indicator data selected to accurately reflect population change. Hence, prior knowledge as to the characteristics of the administrative data used as potential population indicators in a regression model is important. This report summarizes the strengths and weaknesses associated with the use of residential hydro accounts in the British Columbia regression based population estimation model.

Description:

This paper describes a method of producing current age/sex specific population estimates for small areas utilizing as inputs total population estimates, birth and death data and estimates of historical residual net migration. An evaluation based on the 1981 Census counts for census divisions and school districts in British Columbia is presented.

Description:

A methodology has been developed for producing population estimates by single years of age and sex for small areas (census divisions and census metropolitan areas). To assure reliability, the estimates by single years of age are grouped into five years and only these grouped data are recomended for dissemination. They are based on the age-sex composition of population from the last census, births by sex, deaths by single years of age and sex, estimates of migration by age and sex, and counts of family allowance recipients in the age group 1-14 years.

Description:

Statistics Canada’s current methodologies forestimating the population of census divisions and census metropolitan areas are the regression-nested and component methods. This paper presents the experience with these estimates for the period 1981 to 1985, focusing on problems encountered with the input data on family allowance recipients.

Description:

There are many people called statisticians who carry out a very diverse set of activities which are labelled statistics. As part of the invited address at the 1985 meeting of the Statistical Society of Canada, the author presents his views and discusses the nature of the relationships between the different types of statisticians.

Description:

Unit and item nonresponse almost always occur in surveys and censuses. The larger its size the larger its potential effect will be on survey estimates. It is, therefore, important to cope with it at every stage where they can be affected. At varying degrees the size of nonresponse can be coped with at design, field and processing stages. The nonresponse problems have an impact on estimation formulas for various statistics as a result of imputations and weight adjustments along with survey weights in the estimates of means, totals, or other statistics. The formulas may be decomposed into components that include response errors, the effect of weight adjustment for unit nonresponse, and the effect of substitution for nonresponse. The impacts of the design, field, and processing stages on the components of the estimates are examined.

Description:

Conventional methods of inference in survey sampling are critically examined. The need for conditioning the inference on recognizable subsets of the population is emphasized. A number of real examples involving random sample sizes are presented to illustrate inferences conditional on the realized sample configuration and associated difficulties. The examples include the following: estimation of (a) population mean under simple random sampling; (b) population mean in the presence of outliers; (c) domain total and domain mean; (d) population mean with two-way stratification; (e) population mean in the presence of non-responses; (f) population mean under general designs. The conditional bias and the conditional variance of estimators of a population mean (or a domain mean or total), and the associated confidence intervals, are examined.

Description:

The cost-variance optimization of the design of the Canadian Labour Force Survey was carried out in two steps. First, the sample designs were optimized for each of the two major area types, the Self-Representing (SR) and the Non-Self-Representing (NSR) areas. Cost models were developed and parameters estimated from a detailed field study and by simulation, while variances were estimated using data from the Census of Population. The scope of the optimization included the allocation of sample to the two stages in the SR design, and the consideration of two alternatives to the old design in NSR areas. The second stage of optimization was the allocation of sample to SR and NSR areas.

Description:

The statistics in this bulletin are derived from the 1999 survey of industrial research and development activities in Canada, which covers firms spending a million dollars or more on the performance or funding of research and development in Canada, and from the administrative data of the Canada Customs and Revenue Agency (CCRA) for firms which spend less than a million dollars on the performance or funding of research and development in Canada. The use of CCRA data results in a small understatement in total figures for the most recent years reported.

Description:

Canada's economic competitiveness depends on scientific and technological development and also on the people responsible for this development, especially those engaged in research and development . The number of research and development personnel is a supplementary measure to the statistics on intramural expenditures on research and development . The Frascati Manual states that "Data on the utilisation of scientific and technical personnel provide concrete measurements for international comparisons of resources devoted to research and development.

Description:

Canadian health research is conducted in universities, teaching hospitals, business enterprises, government laboratories and private non-profit organizations. This research is funded from a variety of sources including public, private, domestic and foreign.

Description:

This service bulletin presents the geographic distribution of federal government science and technology expenditures. Data on federal government expenditures on science and technology are found in Volume 24, No. 5 of this publication, released in November, 2000. In both this and the earlier bulletin, science and technology (S&T) expenditures are the sum of expenditures on research and development (R&D) and on related scientific activities (RSA).

Description:

This release provides data on the Research and development activities of the private non-profit sector. Although the contribution of this sector to the national R&D effort is small in dollar terms, its impact, particularly in the university sector, is significant.Questionnaires were mailed to 94 private non-profit organizations thought to be supporting Research and development activities. Twenty organizations reported performing Research and development.

Description:

The higher education sector is composed of "all universities, colleges of technology and other institutes of post-secondary education, whatever their source of finance or legal status. It also includes all research institutes, experimental stations and clinics operating under the direct control of, or administered by, or associated with higher education establishments."

Description:

Gross domestic expenditures on research and development (GERD) represents total R&D expenditures performed in a country's national territory during a given year. GERD includes research and development performed within a country and funded from abroad but excludes payments sent abroad for research and development performed in other countries.

Description:

This Bulletin provides recent information on the performance and funding of Federal Government Expenditures on Scientific Activities, 2000-2001. The statistics presented are derived from the survey of the science and technology (S&T) activities of Federal departments and agencies. According to international convention, S&T is divided into two fields; Natural Sciences and Engineering (NSE) and Social Sciences and Humanities (SSH). These fields of science are further divided into Research and Development (R&D) and Related Scientific Activities (RSA).

Description:

Statistics presented are derived from a survey of nine Provincial Research Organizations (PRO): the InNOVAcorp (formerly the Nova Scotia Research Foundation Corporation), the New Brunswick Research and Productivity Council, the "Centre de recherche industrielle du Québec (CRIQ)", the Industrial Technology Centre (Manitoba) (formerly the Economic Innovation and Technology Council), the Saskatchewan Research Council, the Alberta Research Council, the Yukon Research Institute, the NUNAVUT Research Institute (formerly the Science Institute of the Northwest Territories) and the Aurora Research Institute.

Description:

Updates on expenditures and personnel.

Description: This study presents an updated sociodemographic profile of children aged 0 to 14 years with affirmative responses largely based on parent reports to the questions on the 2021 Census long-form questionnaire about difficulties with activities of daily living.

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: 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.

Description: 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.

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.

Description: Papers in this series provide background discussions of the methods used to develop data for economic, health, and social analytical studies at Statistics Canada. They are intended to provide readers with information on the statistical methods, standards and definitions used to develop databases for research purposes. All papers in this series have undergone peer and institutional review to ensure that they conform to Statistics Canada's mandate and adhere to generally accepted standards of good professional practice.

Description: The Analytical Studies Branch Research Paper Series provides for the circulation of research conducted by Analytical Studies and Modelling Branch staff and collaborators. The Series is intended to stimulate discussion 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. Readers of the Series are encouraged to contact the authors with their comments and suggestions. All the papers in the Analytical Studies Branch Research Paper Series go through institutional and 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.

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.

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.

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.

Description: 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.

Description: 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.