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1. Longitudinal Immigration Database (IMDB) Technical Report, 2024
Surveys and statistical programs – Documentation: 11-633-X2025004
Description: The Longitudinal Immigration Database (IMDB) is a comprehensive source of data that plays a key role in the understanding of the economic behaviour of immigrants. It is the only annual Canadian dataset that allows users to study the characteristics of immigrants to Canada at the time of admission and their economic outcomes and regional (inter-provincial) mobility over a time span of more than 40 years.
Release date: 2025-12-08
2. Statistics Canada International Symposium Series: Proceedings
Journals and periodicals: 11-522-X
Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
Release date: 2025-09-08
3. Bridging BigData and sampling methodology: What is big and where is the bridge?
Articles and reports: 12-001-X202500100009
Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.
Release date: 2025-06-30
4. Comments by Risto Lehtonen on “Progress in survey science and practice: Yesterday-today-tomorrow”
Articles and reports: 12-001-X202500100018
Description: In his article, Professor Carl-Erik Särndal presents for sample-based statistics a new conceptual framework with only a few key assumptions. Selected aspects of the research tradition in Survey Science are briefly discussed in my comments.
Release date: 2025-06-30
5. Census Technical Report: Coverage
Surveys and statistical programs – Documentation: 98-303-X
Description: The Coverage Technical Report will present the errors included in census data that result from persons who are either missed (not enumerated) or enumerated more than once. The population coverage error is one of the most important types of errors because it affects the accuracy of not only population counts, but also all the census data results that describe the characteristics of the population universe.
Release date: 2024-10-23
6. Comments by Aditi Sen on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
Articles and reports: 12-001-X202400100010
Description: 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
7. Improvements to the Canadian Income Survey Methodology for the 2022 Reference Year
Articles and reports: 75F0002M2024005
Description: 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
8. ABS DataLab output checking tools Archived
Articles and reports: 11-522-X202200100006
Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.
Release date: 2024-03-25
9. Census of Agriculture: Data quality report
Surveys and statistical programs – Documentation: 32-26-0007
Description: Census of Agriculture data provide statistical information on farms and farm operators at fine geographic levels and for small subpopulations. Quality evaluation activities are essential to ensure that census data are reliable and that they meet user needs.
This report provides data quality information pertaining to the Census of Agriculture, such as sources of error, error detection, disclosure control methods, data quality indicators, response rates and collection rates.
Release date: 2024-02-06
10. Mapping Production Activity in Yukon: Experimental Indexes of Grid Square-based Gross Domestic Product
Articles and reports: 11-633-X2023003
Description: 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

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1. Statistics Canada International Symposium Series: Proceedings
Journals and periodicals: 11-522-X
Description: Since 1984, an annual international symposium on methodological issues has been sponsored by Statistics Canada. Proceedings have been available since 1987.
Release date: 2025-09-08
2. Bridging BigData and sampling methodology: What is big and where is the bridge?
Articles and reports: 12-001-X202500100009
Description: BigData users and the BigData research community are expanding rapidly, while statisticians at large are seemingly becoming divided between those who are enthusiastic and those who are concerned, if not downright hostile. Is BigData also a big step ahead, truly advancing our ability to extract meaningful information and actual knowledge from data? Is BigData underplaying traditional statistical inference as we know it, supplanting survey methodology as a low-cost futuristic option? In this paper I will attempt to unravel the multifaceted relationship bridging BigData to sampling methodology. Starting by reasoning why it should be interesting to look at BigData from a sampling statistician’s perspective, I will delve deeper into the somewhat ambiguous definition of BigData and share some very personal considerations and views on the matter. In the process, several open questions will arise while discussing a personal selection of insights that are traceable through the vast body of statistical literature around BigData and sampling methodology. The discussion will take various angles explored across nine key points, and it will conclude with a forward-looking perspective on a main challenge for future research: addressing the strong assumptions needed to manage deviations from purely randomized data collection.
Release date: 2025-06-30
3. Comments by Risto Lehtonen on “Progress in survey science and practice: Yesterday-today-tomorrow”
Articles and reports: 12-001-X202500100018
Description: In his article, Professor Carl-Erik Särndal presents for sample-based statistics a new conceptual framework with only a few key assumptions. Selected aspects of the research tradition in Survey Science are briefly discussed in my comments.
Release date: 2025-06-30
4. Comments by Aditi Sen on “Exploring the assumption that commercial online nonprobability survey respondents are answering in good faith”
Articles and reports: 12-001-X202400100010
Description: 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
5. Improvements to the Canadian Income Survey Methodology for the 2022 Reference Year
Articles and reports: 75F0002M2024005
Description: 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
6. ABS DataLab output checking tools Archived
Articles and reports: 11-522-X202200100006
Description: The Australian Bureau of Statistics (ABS) is committed to improving access to more microdata, while ensuring privacy and confidentiality is maintained, through its virtual DataLab which supports researchers to undertake complex research more efficiently. Currently, the DataLab research outputs need to follow strict rules to minimise disclosure risks for clearance. However, the clerical-review process is not cost effective and has potential to introduce errors. The increasing number of statistical outputs from different projects can potentially introduce differencing risks even though these outputs from different projects have met the strict output rules. The ABS has been exploring the possibility of providing automatic output checking using the ABS cellkey methodology to ensure that all outputs across different projects are protected consistently to minimise differencing risks and reduce costs associated with output checking.
Release date: 2024-03-25
7. Mapping Production Activity in Yukon: Experimental Indexes of Grid Square-based Gross Domestic Product
Articles and reports: 11-633-X2023003
Description: 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
8. Improvements to the Canadian Income Survey Methodology for the 2021 Reference Year
Articles and reports: 75F0002M2023005
Description: The Canadian Income Survey (CIS) has introduced improvements to the methods and systems used to produce income estimates with the release of its 2021 reference year estimates. This paper describes the changes and presents the approximate net result of these changes on income estimates using data for 2019 and 2020. The changes described in this paper highlight the ways in which data quality has been improved while producing minimal impact on key CIS estimates and trends.
Release date: 2023-08-29
9. Data Quality as Fitness for Use Archived
Stats in brief: 89-20-00062023001
Description: 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
10. Understanding Confidence Intervals for the 2021 Census
Articles and reports: 98-20-00012021003
Description:
This fact sheet provides a concise description of the context to the understanding of confidence intervals. Confidence intervals are a useful data quality indicator. Confidence intervals will usually be available in data tables accessible through the Statistics Canada website.

Release date: 2022-09-21

Reference (42)

Reference (42) (30 to 40 of 42 results)

31. User Guide for the Survey of Household Spending, 2001 Archived
Surveys and statistical programs – Documentation: 62F0026M2002002
Geography: Province or territory
Description:
This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via paper questionnaires and personal interviews conducted in January, February and March after the reference year. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the 10 provinces and the 3 territories. (The territories are surveyed every second year, starting in 2001.) This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share and aggregates).
Release date: 2002-12-11
32. Data collection methods for the 2001 Census of Agriculture Archived
Surveys and statistical programs – Documentation: 11-522-X20010016234
Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
With the goal of obtaining a complete enumeration of the Canadian agricultural sector, the 2001 Census of Agriculture has been conducted using several collection methods. Challenges to the traditional drop-off and mail-back of paper questionnaires in a household-based enumeration have led to the adoption of supplemental methods using newer technologies to maintain the coverage and content of the census. Overall, this mixed-mode data collection process responds to the critical needs of the census programme at various points. This paper examines these data collection methods, several quality assessments, and the future challenges of obtaining a co-ordinated view of the methods' individual approaches to achieving data quality.
Release date: 2002-09-12
33. Nonresponse bias analyses at the National Center for Education Statistics Archived
Surveys and statistical programs – Documentation: 11-522-X20010016269
Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. It is intended for an audience of survey methodologists.
In surveys with low response rates, non-response bias can be a major concern. While it is not always possible to measure the actual bias due to non-response, there are different approaches that help identify potential sources of non-response bias. In the National Center for Education Statistics (NCES), surveys with a response rate lower than 70% must conduct a non-response bias analysis. This paper discusses the different approaches to non-response bias analyses using examples from NCES.
Release date: 2002-09-12
34. User Guide - Survey of Household Spending, 2000 Archived
Surveys and statistical programs – Documentation: 62F0026M2001004
Geography: Province or territory
Description:
This guide presents information of interest to users of data from the Survey of Household Spending. Data are collected via personal interview conducted in January, February and March after the reference year using a paper questionnaire. Information is gathered about the spending habits, dwelling characteristics and household equipment of Canadian households during the reference year. The survey covers private households in the ten provinces. (The three territories are surveyed every second year starting in 2001.)
This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. There is also a section describing the various statistics that can be created using expenditure data (e.g., budget share, market share, and aggregates).
Release date: 2001-12-12
35. An Overview of the Issues Related to the Use of Personal Identifiers Archived
Surveys and statistical programs – Documentation: 85-602-X
Description:
The purpose of this report is to provide an overview of existing methods and techniques making use of personal identifiers to support record linkage. Record linkage can be loosely defined as a methodology for manipulating and / or transforming personal identifiers from individual data records from one or more operational databases and subsequently attempting to match these personal identifiers to create a composite record about an individual. Record linkage is not intended to uniquely identify individuals for operational purposes; however, it does provide probabilistic matches of varying degrees of reliability for use in statistical reporting. Techniques employed in record linkage may also be of use for investigative purposes to help narrow the field of search against existing databases when some form of personal identification information exists.
Release date: 2000-12-05
36. Integration of Administrative Data with Survey and Census Data Archived
Surveys and statistical programs – Documentation: 21-601-M1999042
Description:
This paper reconstructs the development and evolution of the Canadian agricultural statistical system. It describes the expanding and increasingly important role of administrative data, which is integrated into survey and census information in order to complement, supplement or replace survey information or to assist with frame maintenance.
Release date: 2000-01-14
37. Utilization of Document Imaging Technology by the 1996 Canadian Census of Agriculture Archived
Surveys and statistical programs – Documentation: 21-601-M1998034
Description:
This paper describes the experiences, the issues and the expectations of the many different players involved in the implementation of document imaging for the Canadian Census of Agriculture.
Release date: 2000-01-13
38. Qualitative Aspects of the Survey of Labour and Income Dynamics (SLID) Test 3A Data Collection Archived
Surveys and statistical programs – Documentation: 75F0002M1993007
Description:
This report presents a summary evaluation of the quality of the data collected during the Survey of Labour and Income Dynamics (SLID) field test of labour market activity data, held in January and February 1993.
Release date: 1995-12-30
39. The Survey of Labour and Income Dynamics (SLID) Content Evaluation, the Authority Series: Supervision and Management Archived
Surveys and statistical programs – Documentation: 75F0002M1993009
Description:
This paper presents an analysis of the questions in the Survey of Labour and Income Dynamics (SLID) relating to supervision and management. It uses data collected in January 1993.
Release date: 1995-12-30
40. Qualitative Aspects of the Survey of Labour and Income Dynamics (SLID) Test 3B Data Collection Archived
Surveys and statistical programs – Documentation: 75F0002M1993011
Description:
This report presents a summary evaluation of the quality of the data collected during the Survey of Labour and Income Dynamics (SLID) field test of income and wealth, held in April and May 1993.
Release date: 1995-12-30

Date modified:: 2026-08-13