Analysis
Filter results by
Search HelpKeyword(s)
Subject
- Selected: Statistical methods (191)
- Administrative data (12)
- Collection and questionnaires (6)
- Data analysis (31)
- Disclosure control and data dissemination (8)
- Editing and imputation (5)
- Frames and coverage (3)
- History and context (9)
- Inference and foundations (22)
- Quality assurance (6)
- Response and nonresponse (15)
- Simulations (1)
- Statistical techniques (26)
- Survey design (19)
- Time series (2)
- Weighting and estimation (53)
- Other content related to Statistical methods (24)
Year of publication
Author(s)
Survey or statistical program
- Canadian Income Survey (9)
- Census of Population (7)
- Labour Force Survey (5)
- Longitudinal and International Study of Adults (5)
- Consumer Price Index (4)
- Longitudinal Immigration Database (4)
- Canadian Community Health Survey - Annual Component (3)
- Distributions of household economic accounts for wealth of Canadian households (3)
- Vital Statistics - Death Database (2)
- Survey of Household Spending (2)
- Canadian Health Measures Survey (2)
- Gross Domestic Product by Industry - National (Monthly) (1)
- National Balance Sheet Accounts (1)
- Monthly Oil and Other Liquid Petroleum Products Pipeline Survey (1)
- Annual Electricity Supply and Disposition Survey (1)
- Survey of Employment, Payrolls and Hours (1)
- Survey of Financial Security (1)
- Monthly Passenger Bus and Urban Transit Survey (1)
- Stock and Consumption of Fixed Non-residential Capital (1)
- Tuition and Living Accommodation Costs (1)
- Canadian Cancer Registry (1)
- Indigenous Peoples Survey (1)
- Uniform Crime Reporting Survey (1)
- Households and the Environment Survey (1)
- Survey of Labour and Income Dynamics (1)
- Annual Income Estimates for Census Families and Individuals (T1 Family File) (1)
- Air Quality Indicators (1)
- Biennial Drinking Water Plants Survey (1)
- Gross Domestic Expenditures on Research and Development (1)
- Canadian National Health Survey (1)
- Survey of Safety in Public and Private Spaces (1)
- Canadian Housing Statistics Program (1)
- Canadian Housing Survey (1)
- Survey on Early Learning and Child Care Arrangements (SELCCA) (1)
- Canadian Perspectives Survey Series (CPSS) (1)
- Canadian Survey on Business Conditions (1)
- Canada Mortgage and Housing Corporation (1)
Results
All (191)
All (191) (180 to 190 of 191 results)
- Articles and reports: 11F0019M2019025Description:
This study identifies gig workers based on characteristics of their work arrangements and how these are reported in tax data. It introduces a definition of gig work specific to the way work arrangements are reported in the Canadian tax system and estimates the size of the gig economy in Canada using administrative data. The share of gig workers among all workers rose from 5.5% in 2005 to 8.2% in 2016. Some of this increase coincided with the introduction and proliferation of online platforms. The analysis highlights gender differences in the trends and characteristics of gig workers. By linking administrative data to 2016 Census microdata, this study also examines educational and occupational differences in the prevalence of gig workers.
Release date: 2019-12-16 - Journals and periodicals: 92F0138MDescription:
The Geography working paper series is intended to stimulate discussion on a variety of topics covering conceptual, methodological or technical work to support the development and dissemination of the division's data, products and services. Readers of the series are encouraged to contact the Geography Division with comments and suggestions.
Release date: 2019-11-13 - Articles and reports: 11-633-X2019004Description:
This paper shows how to estimate the effect of the Canada-United States border on non-energy goods trade at a sub-provincial/state level using Statistics Canada’s Surface Transportation File (STF), augmented with United States domestic trade data. It uses a gravity model framework to compare cross-border to domestic trade flows among 201 Canadian and United States regions in year 2012. It shows that some 25 years after the Canada-United States Free Trade Agreement (the North American Free Trade Agreement’s predecessor) was ratified, the cost of trading goods across the border still amounts to a 30% tariff on bilateral trade between Canadian and United States regions. The paper also demonstrates how these estimates can be used along with general equilibrium Poisson pseudo maximum likelihood (GEPPML) methods to describe the effect of changing border costs on North American trade patterns and regional welfare.
Release date: 2019-09-24 - Journals and periodicals: 89-20-0001Description:
Historical works allow readers to peer into the past, not only to satisfy our curiosity about “the way things were,” but also to see how far we’ve come, and to learn from the past. For Statistics Canada, such works are also opportunities to commemorate the agency’s contributions to Canada and its people, and serve as a reminder that an institution such as this continues to evolve each and every day.
On the occasion of Statistics Canada’s 100th anniversary in 2018, Standing on the shoulders of giants: History of Statistics Canada: 1970 to 2008, builds on the work of two significant publications on the history of the agency, picking up the story in 1970 and carrying it through the next 36 years, until 2008. To that end, when enough time has passed to allow for sufficient objectivity, it will again be time to document the agency’s next chapter as it continues to tell Canada’s story in numbers.
Release date: 2018-12-03 - Journals and periodicals: 12-605-XDescription:
The Record Linkage Project Process Model (RLPPM) was developed by Statistics Canada to identify the processes and activities involved in record linkage. The RLPPM applies to linkage projects conducted at the individual and enterprise level using diverse data sources to create new data sources to meet analytical and operational needs.
Release date: 2017-06-05 - Journals and periodicals: 11-634-XDescription:
This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.
Release date: 2016-07-06 - Journals and periodicals: 88F0006XGeography: CanadaDescription:
Statistics Canada is engaged in the "Information System for Science and Technology Project" to develop useful indicators of activity and a framework to tie them together into a coherent picture of science and technology (S&T) in Canada. The working papers series is used to publish results of the different initiatives conducted within this project. The data are related to the activities, linkages and outcomes of S&T. Several key areas are covered such as: innovation, technology diffusion, human resources in S&T and interrelations between different actors involved in S&T. This series also presents data tabulations taken from regular surveys on research and development (R&D) and S&T and made possible by the project.
Release date: 2011-12-23 - Journals and periodicals: 12-587-XDescription:
This publication shows readers how to design and conduct a census or sample survey. It explains basic survey concepts and provides information on how to create efficient and high quality surveys. It is aimed at those involved in planning, conducting or managing a survey and at students of survey design courses.
This book contains the following information:
-how to plan and manage a survey;-how to formulate the survey objectives and design a questionnaire; -things to consider when determining a sample design (choosing between a sample or a census, defining the survey population, choosing a survey frame, identifying possible sources of survey error); -choosing a method of collection (self-enumeration, personal interviews or telephone interviews; computer-assisted versus paper-based questionnaires); -organizing and conducting data collection operations;-determining the sample size, allocating the sample across strata and selecting the sample; -methods of point estimation and variance estimation, and data analysis; -the use of administrative data, particularly during the design and estimation phases-how to process the data (which consists of all data handling activities between collection and estimation) and use quality control and quality assurance measures to minimize and control errors during various survey steps; and-disclosure control and data dissemination.
This publication also includes a case study that illustrates the steps in developing a household survey, using the methods and principles presented in the book. This publication was previously only available in print format and originally published in 2003.
Release date: 2010-09-27 - Articles and reports: 11-536-XDescription:
On October 31 and November 1, 2007, Statistics Canada held a special methodology conference in honour of Professor Carl-Erik Särndal entitled Workshop on Calibration and Estimation in Surveys (WCES). The workshop focused on diverse aspects of Professor Särndal's career - his work, teachings and writings having had a profound affect on the way methodologists carry out their daily duties, both here and abroad. He was a consultant to Statistics Canada for many years and is a member of the Advisory Committee on Statistical Methods. Professor Särndal's deep and lasting influence in this field earned him the 2007 Waksberg Award, one of the most prestigious honours a statistician can receive in recognition of his or her work in survey sampling statistics.
Release date: 2009-08-11 - Journals and periodicals: 89-639-XGeography: CanadaDescription:
Beginning in late 2006, the Social and Aboriginal Statistics Division of Statistics Canada embarked on the process of review of questions used in the Census and in surveys to produce data about Aboriginal peoples (North American Indian, Métis and Inuit). This process is essential to ensure that Aboriginal identification questions are valid measures of contemporary Aboriginal identification, in all its complexity. Questions reviewed included the following (from the Census 2B questionnaire):- the Ethnic origin / Aboriginal ancestry question;- the Aboriginal identity question;- the Treaty / Registered Indian question; and- the Indian band / First Nation Membership question.
Additional testing was conducted on Census questions with potential Aboriginal response options: the population group question (also known as visible minorities), and the Religion question. The review process to date has involved two major steps: regional discussions with data users and stakeholders, and qualitative testing. The regional discussions with over 350 users of Aboriginal data across Canada were held in early 2007 to examine the four questions used on the Census and other surveys of Statistics Canada. Data users included National Aboriginal organizations, Aboriginal Provincial and Territorial Organizations, Federal, Provincial and local governments, researchers and Aboriginal service organizations. User feedback showed that main areas of concern were data quality, undercoverage, the wording of questions, and the importance of comparability over time.
Release date: 2009-04-17
- Previous Go to previous page of All results
- 1 Go to page 1 of All results
- ...
- 14 Go to page 14 of All results
- 15 Go to page 15 of All results
- 16 Go to page 16 of All results
- 17 Go to page 17 of All results
- 18 Go to page 18 of All results
- 19 (current) Go to page 19 of All results
- 20 Go to page 20 of All results
- Next Go to next page of All results
Stats in brief (12)
Stats in brief (12) (0 to 10 of 12 results)
- Stats in brief: 89-20-00062024001Description: This short video explains how it can be very effective for all levels of governments and organizations that serve communities to use disaggregated data to make evidence-informed public policy decisions. By using disaggregated data, policymakers are able to design more appropriate and effective policies that meet the needs of each diverse and unique Canadian.Release date: 2024-07-16
- Stats in brief: 89-20-00062024002Description: This short video explains how the use of disaggregated data can help policymakers to develop more targeted and effective policies by identifying the unique needs and challenges faced by different demographic groups.Release date: 2024-07-16
- Stats in brief: 11-001-X202411338008Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-04-22
- Stats in brief: 11-637-XDescription: This product presents data on the Sustainable Development Goals. They present an overview of the 17 Goals through infographics by leveraging data currently available to report on Canada’s progress towards the 2030 Agenda for Sustainable Development.Release date: 2024-01-25
- Stats in brief: 11-001-X202402237898Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-01-22
- Stats in brief: 89-20-00062023001Description: This course is intended for Government of Canada employees who would like to learn about evaluating the quality of data for a particular use. Whether you are a new employee interested in learning the basics, or an experienced subject matter expert looking to refresh your skills, this course is here to help.Release date: 2023-07-17
- Stats in brief: 98-20-00032021011Description: This video explains the key concepts of different levels of aggregation of income data such as household and family income; income concepts derived from key income variables such as adjusted income and equivalence scale; and statistics used for income data such as median and average income, quartiles, quintiles, deciles and percentiles.Release date: 2023-03-29
- Stats in brief: 98-20-00032021012Description: This video builds on concepts introduced in the other videos on income. It explains key low-income concepts - Market Basket Measure (MBM), Low income measure (LIM) and Low-income cut-offs (LICO) and the indicators associated with these concepts such as the low-income gap and the low-income ratio. These concepts are used in analysis of the economic well-being of the population.Release date: 2023-03-29
- Stats in brief: 11-001-X202231822683Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2022-11-14
- Stats in brief: 89-20-00062022004Description:
Gathering, exploring, analyzing and interpreting data are essential steps in producing information that benefits society, the economy and the environment. In this video, we will discuss the importance of considering data ethics throughout the process of producing statistical information.
As a pre-requisite to this video, make sure to watch the video titled “Data Ethics: An introduction” also available in Statistics Canada’s data literacy training catalogue.
Release date: 2022-10-17
Articles and reports (166)
Articles and reports (166) (0 to 10 of 166 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
- Previous Go to previous page of Articles and reports results
- 1 (current) Go to page 1 of Articles and reports results
- 2 Go to page 2 of Articles and reports results
- 3 Go to page 3 of Articles and reports results
- 4 Go to page 4 of Articles and reports results
- 5 Go to page 5 of Articles and reports results
- 6 Go to page 6 of Articles and reports results
- 7 Go to page 7 of Articles and reports results
- ...
- 17 Go to page 17 of Articles and reports results
- Next Go to next page of Articles and reports results
Journals and periodicals (13)
Journals and periodicals (13) (0 to 10 of 13 results)
- Journals and periodicals: 11-522-XDescription: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.Release date: 2024-06-28
- Journals and periodicals: 12-001-XGeography: CanadaDescription: The journal publishes articles dealing with various aspects of statistical development relevant to a statistical agency, such as design issues in the context of practical constraints, use of different data sources and collection techniques, total survey error, survey evaluation, research in survey methodology, time series analysis, seasonal adjustment, demographic studies, data integration, estimation and data analysis methods, and general survey systems development. The emphasis is placed on the development and evaluation of specific methodologies as applied to data collection or the data themselves.Release date: 2024-06-25
- Journals and periodicals: 75F0002MDescription: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.Release date: 2024-04-26
- Journals and periodicals: 11-633-XDescription: 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.Release date: 2024-01-22
- Journals and periodicals: 12-206-XDescription: 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
- Journals and periodicals: 92F0138MDescription:
The Geography working paper series is intended to stimulate discussion on a variety of topics covering conceptual, methodological or technical work to support the development and dissemination of the division's data, products and services. Readers of the series are encouraged to contact the Geography Division with comments and suggestions.
Release date: 2019-11-13 - Journals and periodicals: 89-20-0001Description:
Historical works allow readers to peer into the past, not only to satisfy our curiosity about “the way things were,” but also to see how far we’ve come, and to learn from the past. For Statistics Canada, such works are also opportunities to commemorate the agency’s contributions to Canada and its people, and serve as a reminder that an institution such as this continues to evolve each and every day.
On the occasion of Statistics Canada’s 100th anniversary in 2018, Standing on the shoulders of giants: History of Statistics Canada: 1970 to 2008, builds on the work of two significant publications on the history of the agency, picking up the story in 1970 and carrying it through the next 36 years, until 2008. To that end, when enough time has passed to allow for sufficient objectivity, it will again be time to document the agency’s next chapter as it continues to tell Canada’s story in numbers.
Release date: 2018-12-03 - Journals and periodicals: 12-605-XDescription:
The Record Linkage Project Process Model (RLPPM) was developed by Statistics Canada to identify the processes and activities involved in record linkage. The RLPPM applies to linkage projects conducted at the individual and enterprise level using diverse data sources to create new data sources to meet analytical and operational needs.
Release date: 2017-06-05 - Journals and periodicals: 11-634-XDescription:
This publication is a catalogue of strategies and mechanisms that a statistical organization should consider adopting, according to its particular context. This compendium is based on lessons learned and best practices of leadership and management of statistical agencies within the scope of Statistics Canada’s International Statistical Fellowship Program (ISFP). It contains four broad sections including, characteristics of an effective national statistical system; core management practices; improving, modernizing and finding efficiencies; and, strategies to better inform and engage key stakeholders.
Release date: 2016-07-06 - Journals and periodicals: 88F0006XGeography: CanadaDescription:
Statistics Canada is engaged in the "Information System for Science and Technology Project" to develop useful indicators of activity and a framework to tie them together into a coherent picture of science and technology (S&T) in Canada. The working papers series is used to publish results of the different initiatives conducted within this project. The data are related to the activities, linkages and outcomes of S&T. Several key areas are covered such as: innovation, technology diffusion, human resources in S&T and interrelations between different actors involved in S&T. This series also presents data tabulations taken from regular surveys on research and development (R&D) and S&T and made possible by the project.
Release date: 2011-12-23
- Date modified: