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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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Analysis (94)

Analysis (94) (10 to 20 of 94 results)

11. Created Equal Archived
Stats in brief: 45-20-00032022002
Description: 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
12. Measuring the undercoverage of two data sources with a nearly perfect coverage through capture and recapture in the presence of linkage errors Archived
Articles and reports: 11-522-X202100100006
Description:
In the context of its "admin-first" paradigm, Statistics Canada is prioritizing the use of non-survey sources to produce official statistics. This paradigm critically relies on non-survey sources that may have a nearly perfect coverage of some target populations, including administrative files or big data sources. Yet, this coverage must be measured, e.g., by applying the capture-recapture method, where they are compared to other sources with good coverage of the same populations, including a census. However, this is a challenging exercise in the presence of linkage errors, which arise inevitably when the linkage is based on quasi-identifiers, as is typically the case. To address the issue, a new methodology is described where the capture-recapture method is enhanced with a new error model that is based on the number of links adjacent to a given record. It is applied in an experiment with public census data.
Key Words: dual system estimation, data matching, record linkage, quality, data integration, big data.

Release date: 2021-10-22
13. Data Quality in Six Dimensions Archived
Stats in brief: 89-20-00062020001
Description:
In this video, you will be introduced to the fundamentals of data quality, which can be summed up in six dimensions—or six different ways to think about quality. You will also learn how each dimension can be used to evaluate the quality of data.
Release date: 2020-09-23
14. Data Accuracy and Validation: Methods to ensure the quality of data Archived
Stats in brief: 89-20-00062020008
Description:
Accuracy is one of the six dimensions of Data Quality used at Statistics Canada. Accuracy refers to how well the data reflects the truth or what actually happened. In this video we will present methods to describe accuracy in terms of validity and correctness. We will also discuss methods to validate and check the accuracy of data values.
Release date: 2020-09-23
15. Revising the classification of founded and unfounded criminal incidents in the Uniform Crime Reporting Survey Archived
Articles and reports: 85-002-X201800154973
Description:
This Juristat article provides information on the collection, through the Uniform Crime Reporting Survey, of unfounded criminal incidents in Canada, including sexual assaults. It will provide background on the collection of these data and an overview of the actions taken by the Canadian Centre for Justice Statistics - a division at Statistics Canada - and the Police Information and Statistics Committee of the Canadian Association of Chiefs of Police to revise the Uniform Crime Reporting Survey to address data quality and reporting issues, and to reinstate collection of information on unfounded criminal incidents.
Release date: 2018-07-12
16. Hiring and Layoff Rates by Economic Region of Residence: Data Quality, Concepts and Methods Archived
Articles and reports: 11-633-X2016001
Description:
Every year, thousands of workers lose their jobs as firms reduce the size of their workforce in response to growing competition, technological changes, changing trade patterns and numerous other factors. Thousands of workers also start a job with a new employer as new firms enter a product market and existing firms expand or replace employees who recently left. This worker reallocation process across employers is generally seen as contributing to productivity growth and rising living standards. To measure this labour reallocation process, labour market indicators such as hiring rates and layoff rates are needed. In response to growing demand for subprovincial labour market information and taking advantage of unique administrative datasets, Statistics Canada is producing hiring rates and layoff rates by economic region of residence. This document describes the data sources, conceptual and methodological issues, and other matters pertaining to these two indicators.
Release date: 2016-06-27
17. The relevance of follow ups in data collection for the Quality Assurance system of the Portuguese Population and Housing Census Archived
Articles and reports: 12-001-X201500114162
Description:
The operationalization of the Population and Housing Census in Portugal is managed by a hierarchical structure in which Statistics Portugal is at the top and local government institutions at the bottom. When the Census takes place every ten years, local governments are asked to collaborate with Statistics Portugal in the execution and monitoring of the fieldwork operations at the local level. During the Pilot Test stage of the 2011 Census, local governments were asked for additional collaboration: to answer the Perception of Risk survey, whose aim was to gather information to design a quality assurance instrument that could be used to monitor the Census operations. The response rate of the survey was desired to be 100%, however, by the deadline of data collection nearly a quarter of local governments had not responded to the survey and thus a decision was made to make a follow up mailing. In this paper, we examine whether the same conclusions could have been reached from survey without follow ups as with them and evaluate the influence of follow ups on the conception of the quality assurance instrument. Comparison of responses on a set of perception variables revealed that local governments answering previous or after the follow up did not differ. However the configuration of the quality assurance instrument changed when including follow up responses.
Release date: 2015-06-29
18. Optimizing quality of response through adaptive survey designs Archived
Articles and reports: 12-001-X201300111824
Description:
In most surveys all sample units receive the same treatment and the same design features apply to all selected people and households. In this paper, it is explained how survey designs may be tailored to optimize quality given constraints on costs. Such designs are called adaptive survey designs. The basic ingredients of such designs are introduced, discussed and illustrated with various examples.
Release date: 2013-06-28
19. Automatic editing with hard and soft edits Archived
Articles and reports: 12-001-X201300111825
Description:
A considerable limitation of current methods for automatic data editing is that they treat all edits as hard constraints. That is to say, an edit failure is always attributed to an error in the data. In manual editing, however, subject-matter specialists also make extensive use of soft edits, i.e., constraints that identify (combinations of) values that are suspicious but not necessarily incorrect. The inability of automatic editing methods to handle soft edits partly explains why in practice many differences are found between manually edited and automatically edited data. The object of this article is to present a new formulation of the error localisation problem which can distinguish between hard and soft edits. Moreover, it is shown how this problem may be solved by an extension of the error localisation algorithm of De Waal and Quere (2003).
Release date: 2013-06-28
20. Historical Data Linkage of Tax Records on Labour and Income: The Case of the Living in Canada Survey Pilot Archived
Articles and reports: 89-648-X2013002
Geography: Canada
Description:
Data matching is a common practice used to reduce the response burden of respondents and to improve the quality of the information collected from respondents when the linkage method does not introduce bias. However, historical linkage, which consists in linking external records from previous years to the year of the initial wave of a survey, is relatively rare and, until now, had not been used at Statistics Canada. The present paper describes the method used to link the records from the Living in Canada Survey pilot to historical tax data on income and labour (T1 and T4 files). It presents the evolution of the linkage rate going back over time and compares earnings data collected from personal income tax returns with those collected from employers file. To illustrate the new possibilities of analysis offered by this type of linkage, the study concludes with an earnings profile by age and sex for different cohorts based on year of birth.
Release date: 2013-01-24

Reference (42)

Reference (42) (10 to 20 of 42 results)

11. National Household Survey User Guide, 2011 Archived
Surveys and statistical programs – Documentation: 99-001-X2011001
Description:
The National Household Survey User Guide is a reference document that describes the various phases of the National Household Survey (NHS). It provides an overview of the 2011 NHS content, sampling design and collection, data processing, data quality assessment and data dissemination. The National Household Survey User Guide may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2011 NHS.
Release date: 2013-05-08
12. Overview of the Census
Surveys and statistical programs – Documentation: 98-302-X
Description:
The Overview of the Census is a reference document covering each phase of the Census of Population and Census of Agriculture. It provides an overview of the 2011 Census from legislation governing the census to content determination, collection, processing, data quality assessment and data dissemination. It also traces the history of the census from the early days of New France to the present.
In addition, the Overview of the Census informs users about the steps taken to protect confidential information, along with steps taken to verify the data and minimize errors. It also provides information on the possible uses of census data and covers the different levels of geography and the range of products and services available.
The Overview of the Census may be useful to both new and experienced users who wish to familiarize themselves with and find specific information about the 2011 Census. The first part covers the Census of Population, while the second is about the Census of Agriculture.
Release date: 2012-02-08
13. Survey of Household Spending 2009: Data Quality Indicators Archived
Surveys and statistical programs – Documentation: 62F0026M2011001
Description:
This report describes the quality indicators produced for the 2009 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2011-06-16
14. Survey of Household Spending 2007: Data Quality Indicators Archived
Surveys and statistical programs – Documentation: 62F0026M2010004
Description:
This report describes the quality indicators produced for the 2007 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2010-12-13
15. Survey of Household Spending 2008: Data Quality Indicators Archived
Surveys and statistical programs – Documentation: 62F0026M2010005
Description:
This report describes the quality indicators produced for the 2008 Survey of Household Spending. These quality indicators, such as coefficients of variation, nonresponse rates, slippage rates and imputation rates, help users interpret the survey data.
Release date: 2010-12-13
16. Aboriginal Peoples Technical Report, 2006 Census Archived
Surveys and statistical programs – Documentation: 92-569-X
Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
Release date: 2010-02-09
17. Aboriginal Peoples Technical Report, 2006 Census, Second Edition Archived
Surveys and statistical programs – Documentation: 92-569-X2006002
Description:
The 2006 Census Technical Report on Aboriginal Peoples deals with: (i) Aboriginal ancestry, (ii) Aboriginal identity, (iii) registered Indian status, and (iv) First Nation or Band membership. The report aims to inform users about the complexity of the data and any difficulties that could affect their use. It explains the conceptual framework and definitions used to gather the data, and it discusses factors that could affect data quality. The historical comparability of the data is also discussed.
The second edition includes the same content as the first, and new text has been added on data processing (Chapter 3). As well, modified content about data quality and 'on reserve' communities has been incorporated into the original sections.
Release date: 2010-02-09
18. User Guide for the Survey of Household Spending, 2008 Archived
Surveys and statistical programs – Documentation: 62F0026M2009002
Geography: Province or territory
Description:
This guide presents information of interest to users of data from the Survey of Household Spending, which gathers information on the spending habits, dwelling characteristics and household equipment of Canadian households. The survey covers private households in the 10 provinces. (The territories are surveyed every second year, starting in 1999.)
This guide includes definitions of survey terms and variables, as well as descriptions of survey methodology and data quality. One section describes the various statistics that can be created using expenditure data (e.g., budget share, market share, aggregates and medians).
Release date: 2009-12-18
19. Evaluation of the Strengths and Difficulties Questionnaire Archived
Surveys and statistical programs – Documentation: 89-634-X2009008
Geography: Canada
Description:
The Strengths and Difficulties Questionnaire (SDQ) is a parent-reported instrument designed to provide information on children's behaviours and relationships. The SDQ consists of 25 items which are grouped into five subscales: (1) pro-social, (2) inattention-hyperactivity, (3) emotional symptoms, (4) conduct problems, and (5) peer problems. The SDQ was used to provide information on children aged 2 to 5 years in the 2006 Aboriginal Children's Survey (ACS). Though validated on general populations, the constructs of the SDQ have not been validated for off-reserve First Nations, Métis and Inuit children in Canada. The first objective of this evaluation is to examine if the five subscales of the SDQ demonstrate construct validity and reliability for off-reserve First Nations, Métis and Inuit children. The second objective is to examine if an alternative set of subscales, using the 25 SDQ items, may be more valid and reliable for off-reserve First Nations, Métis and Inuit children.
Release date: 2009-11-25
20. Data Quality for the 2006 Survey of Labour and Income Dynamics (SLID) Archived
Surveys and statistical programs – Documentation: 75F0002M2008005
Description: The Survey of Labour and Income Dynamics (SLID) is a longitudinal survey initiated in 1993. The survey was designed to measure changes in the economic well-being of Canadians as well as the factors affecting these changes. Sample surveys are subject to sampling errors. In order to consider these errors, each estimates presented in the "Income Trends in Canada" series comes with a quality indicator based on the coefficient of variation. However, other factors must also be considered to make sure data are properly used. Statistics Canada puts considerable time and effort to control errors at every stage of the survey and to maximise the fitness for use. Nevertheless, the survey design and the data processing could restrict the fitness for use. It is the policy at Statistics Canada to furnish users with measures of data quality so that the user is able to interpret the data properly. This report summarizes the set of quality measures of SLID data. Among the measures included in the report are sample composition and attrition rates, sampling errors, coverage errors in the form of slippage rates, response rates, tax permission and tax linkage rates, and imputation rates.
Release date: 2008-08-20

Date modified:: 2026-08-13