Filter results by
Search HelpCurrently selected filters that can be removed
Keyword(s)
Subject
- Selected: Statistical methods (192)
- Administrative data (12)
- Collection and questionnaires (6)
- Data analysis (32)
- 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 (27)
- Survey design (19)
- Time series (2)
- Weighting and estimation (53)
- Other content related to Statistical methods (23)
Year of publication
13 facets displayed. 0 facets selected.
Author(s)
24 facets displayed. 0 facets selected.
Survey or statistical program
38 facets displayed. 0 facets selected.
- 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)
- Investment Banking Services Price Index (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 (192)
All (192) (10 to 20 of 192 results)
- Articles and reports: 12-001-X202400100011Description: Kennedy, Mercer, and Lau explore misreporting by respondents in non-probability samples and discover a new feature, namely that of deliberate misreporting of demographic characteristics. This finding suggests that the “arms race” between researchers and those determined to disrupt the practice of social science is not over and researchers need to account for such respondents if using high-quality probability surveys to help reduce error in non-probability samples.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100012Description: Nonprobability samples are quick and low-cost and have become popular for some types of survey research. Kennedy, Mercer and Lau examine data quality issues associated with opt-in nonprobability samples frequently used in the United States. They show that the estimates from these samples have serious problems that go beyond representativeness. A total survey error perspective is important for evaluating all types of surveys.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100013Description: Statistical approaches developed for nonprobability samples generally focus on nonrandom selection as the primary reason survey respondents might differ systematically from the target population. Well-established theory states that in these instances, by conditioning on the necessary auxiliary variables, selection can be rendered ignorable and survey estimates will be free of bias. But this logic rests on the assumption that measurement error is nonexistent or small. In this study we test this assumption in two ways. First, we use a large benchmarking study to identify subgroups for which errors in commercial, online nonprobability samples are especially large in ways that are unlikely due to selection effects. Then we present a follow-up study examining one cause of the large errors: bogus responding (i.e., survey answers that are fraudulent, mischievous or otherwise insincere). We find that bogus responding, particularly among respondents identifying as young or Hispanic, is a significant and widespread problem in commercial, online nonprobability samples, at least in the United States. This research highlights the need for statisticians working with commercial nonprobability samples to address bogus responding and issues of representativeness – not just the latter.Release date: 2024-06-25
- Articles and reports: 12-001-X202400100014Description: This paper is an introduction to the special issue on the use of nonprobability samples featuring three papers that were presented at the 29th Morris Hansen Lecture by Courtney Kennedy, Yan Li and Jean-François Beaumont.Release date: 2024-06-25
- 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
- Articles and reports: 75F0002M2024005Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and data sources used to produce income and poverty estimates with the release of its 2022 reference year estimates. Foremost among these improvements is a significant increase in the sample size for a large subset of the CIS content. The weighting methodology was also improved and the target population of the CIS was changed from persons aged 16 years and over to persons aged 15 years and over. This paper describes the changes made and presents the approximate net result of these changes on the income estimates and data quality of the CIS using 2021 data. The changes described in this paper highlight the ways in which data quality has been improved while having little impact on key CIS estimates and trends.Release date: 2024-04-26
- 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
- Stats in brief: 11-001-X202411338008Description: Release published in The Daily – Statistics Canada’s official release bulletinRelease date: 2024-04-22
- Articles and reports: 18-001-X2024001Description: This study applies small area estimation (SAE) and a new geographic concept called Self-contained Labor Area (SLA) to the Canadian Survey on Business Conditions (CSBC) with a focus on remote work opportunities in rural labor markets. Through SAE modelling, we estimate the proportions of businesses, classified by general industrial sector (service providers and goods producers), that would primarily offer remote work opportunities to their workforce.Release date: 2024-04-22
- 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: 2024-03-25
- Previous Go to previous page of All results
- 1 Go to page 1 of All results
- 2 (current) Go to page 2 of All results
- 3 Go to page 3 of All results
- 4 Go to page 4 of All results
- 5 Go to page 5 of All results
- 6 Go to page 6 of All results
- 7 Go to page 7 of All results
- ...
- 20 Go to page 20 of All results
- Next Go to next page of All results
Stats in brief (10)
Stats in brief (10) ((10 results))
- 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 - Stats in brief: 89-20-00062022005Description:
In this video, you will learn the answers to the following questions: What are the different types of error? What are the types of error that lead to statistical bias? Where during the data journey statistical bias can occur?
Release date: 2022-10-17 - 10. Created EqualStats in brief: 45-20-00032022002Description:
Canada’s diversity and rich cultural heritage have been shaped by the people who have come from all over the world to call it home. But even in our multicultural society, eliminating all forms of discrimination remains a challenge. In this episode, we turn a critical eye to the ways that cognitive bias risks perpetuating systemic racism. Statistics are supposed to accurately reflect the world around us, but are all data created equal? Join our guests, Sarah Messou-Ghelazzi, Communications Officer, Filsan Hujaleh, Analyst with the Centre for Social Data Insights and Innovation, and Jeff Latimer, Director General - Accountable for Health, Justice, Diversity and Populations at Statistics Canada as we explore the role data can play to make Canada a more equal society for all.
Release date: 2022-03-16
Articles and reports (169)
Articles and reports (169) (30 to 40 of 169 results)
- Articles and reports: 12-001-X202300200011Description: The article considers sampling designs for populations that can be represented as a N × M matrix. For instance when investigating tourist activities, the rows could be locations visited by tourists and the columns days in the tourist season. The goal is to sample cells (i, j) of the matrix when the number of selections within each row and each column is fixed a priori. The ith row sample size represents the number of selected cells within row i; the jth column sample size is the number of selected cells within column j. A matrix sampling design gives an N × M matrix of sample indicators, with entry 1 at position (i, j) if cell (i, j) is sampled and 0 otherwise. The first matrix sampling design investigated has one level of sampling, row and column sample sizes are set in advance: the row sample sizes can vary while the column sample sizes are all equal. The fixed margins can be seen as balancing constraints and algorithms available for selecting such samples are reviewed. A new estimator for the variance of the Horvitz-Thompson estimator for the mean of survey variable y is then presented. Several levels of sampling might be necessary to account for all the constraints; this involves multi-level matrix sampling designs that are also investigated.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200012Description: In recent decades, many different uses of auxiliary information have enriched survey sampling theory and practice. Jean-Claude Deville contributed significantly to this progress. My comments trace some of the steps on the way to one important theory for the use of auxiliary information: Estimation by calibration.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200013Description: Jean-Claude Deville is one of the most prominent researcher in survey sampling theory and practice. His research on balanced sampling, indirect sampling and calibration in particular is internationally recognized and widely used in official statistics. He was also a pioneer in the field of functional data analysis. This discussion gives us the opportunity to recognize the immense work he has accomplished, and to pay tribute to him. In the first part of this article, we recall briefly his contribution to the functional principal analysis. We also detail some recent extension of his work at the intersection of the fields of functional data analysis and survey sampling. In the second part of this paper, we present some extension of Jean-Claude’s work in indirect sampling. These extensions are motivated by concrete applications and illustrate Jean-Claude’s influence on our work as researchers.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200014Description: Many things have been written about Jean-Claude Deville in tributes from the statistical community (see Tillé, 2022a; Tillé, 2022b; Christine, 2022; Ardilly, 2022; and Matei, 2022) and from the École nationale de la statistique et de l’administration économique (ENSAE) and the Société française de statistique. Pascal Ardilly, David Haziza, Pierre Lavallée and Yves Tillé provide an in-depth look at Jean-Claude Deville’s contributions to survey theory. To pay tribute to him, I would like to discuss Jean-Claude Deville’s contribution to the more day-to-day application of methodology for all the statisticians at the Institut national de la statistique et des études économiques (INSEE) and at the public statistics service. To do this, I will use my work experience, and particularly the four years (1992 to 1996) I spent working with him in the Statistical Methods Unit and the discussions we had thereafter, especially in the 2000s on the rolling census.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200015Description: This article discusses and provides comments on the Ardilly, Haziza, Lavallée and Tillé’s summary presentation of Jean-Claude Deville’s work on survey theory. It sheds light on the context, applications and uses of his findings, and shows how these have become engrained in the role of statisticians, in which Jean-Claude was a trailblazer. It also discusses other aspects of his career and his creative inventions.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200016Description: In this discussion, I will present some additional aspects of three major areas of survey theory developed or studied by Jean-Claude Deville: calibration, balanced sampling and the generalized weight-share method.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200017Description: Jean-Claude Deville, who passed away in October 2021, was one of the most influential researchers in the field of survey statistics over the past 40 years. This article traces some of his contributions that have had a profound impact on both survey theory and practice. This article will cover the topics of balanced sampling using the cube method, calibration, the weight-sharing method, the development of variance expressions of complex estimators using influence function and quota sampling.Release date: 2024-01-03
- Articles and reports: 12-001-X202300200018Description: Sample surveys, as a tool for policy development and evaluation and for scientific, social and economic research, have been employed for over a century. In that time, they have primarily served as tools for collecting data for enumerative purposes. Estimation of these characteristics has been typically based on weighting and repeated sampling, or design-based, inference. However, sample data have also been used for modelling the unobservable processes that gave rise to the finite population data. This type of use has been termed analytic, and often involves integrating the sample data with data from secondary sources. Alternative approaches to inference in these situations, drawing inspiration from mainstream statistical modelling, have been strongly promoted. The principal focus of these alternatives has been on allowing for informative sampling. Modern survey sampling, though, is more focussed on situations where the sample data are in fact part of a more complex set of data sources all carrying relevant information about the process of interest. When an efficient modelling method such as maximum likelihood is preferred, the issue becomes one of how it should be modified to account for both complex sampling designs and multiple data sources. Here application of the Missing Information Principle provides a clear way forward. In this paper I review how this principle has been applied to resolve so-called “messy” data analysis issues in sampling. I also discuss a scenario that is a consequence of the rapid growth in auxiliary data sources for survey data analysis. This is where sampled records from one accessible source or register are linked to records from another less accessible source, with values of the response variable of interest drawn from this second source, and where a key output is small area estimates for the response variable for domains defined on the first source.Release date: 2024-01-03
- Articles and reports: 82-003-X202301200002Description: The validity of survival estimates from cancer registry data depends, in part, on the identification of the deaths of deceased cancer patients. People whose deaths are missed seemingly live on forever and are informally referred to as “immortals”, and their presence in registry data can result in inflated survival estimates. This study assesses the issue of immortals in the Canadian Cancer Registry (CCR) using a recently proposed method that compares the survival of long-term survivors of cancers for which “statistical” cure has been reported with that of similar people from the general population.Release date: 2023-12-20
- Articles and reports: 11-633-X2023003Description: This paper spans the academic work and estimation strategies used in national statistics offices. It addresses the issue of producing fine, grid-level geography estimates for Canada by exploring the measurement of subprovincial and subterritorial gross domestic product using Yukon as a test case.Release date: 2023-12-15
- Previous Go to previous page of Articles and reports results
- 1 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 (current) 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: 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: 11-522-XDescription: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.Release date: 2024-03-25
- 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: