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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) (90 to 100 of 94 results)

91. Some Data Quality Impacts When Merging Survey Data on Income with Tax Data Archived
Articles and reports: 75F0002M1996012
Description:
This paper gives an overview of the different sources of errors that occur with this methodology and presents some results on the impact of this mixed approach. The research has focused on micro-comparisons and has attempted to quantify the impact on measures of change.
Release date: 1997-12-31
92. Consistency of census and vital registration data on older Americans: 1970-1990 Archived
Articles and reports: 12-001-X199500214393
Description:
Major uncertainties about the quality of elderly population and death enumerations in the United States result from coverage and content errors in the censuses and the death registration system. This study evaluates the consistency of reported data between the two sources for the white and the African-American populations. The focus is on the older population (aged 60 and above), where mortality trends have the greatest impact on social programs and where data are most problematic. Using intercensal cohort analysis, age-specific inconsistencies between the sources are identified for two periods: 1970-1980 and 1980-1990. The U.S. data inconsistencies are examined in light of evidence in the literature regarding the nature of coverage and content errors in the data sources. Data for African-Americans are highly inconsistent in the 1970-1990 period, likely the result of age overstatement in censuses relative to death registration. Inconsistencies also exist for whites in the 1970-1980 intercensal period. We argue that the primary source of this error is an undercount in the 1970 census relative to both the 1980 census and the death registration. In contrast, the 1980-1990 data for whites, and particularly for white females, are highly consistent, far better than in most European countries.
Release date: 1995-12-15
93. Comparing telephone and face-to-face interviewing in the United Kingdom Archived
Articles and reports: 12-001-X198700114466
Description:
This paper presents results from methodological experiments comparing telephone and face-to-face interviewing in surveys of the general population. The relatively low level of telephone ownership in the United Kingdom, especially among the less privileged, argues the need for a dual-mode approach combining telephone interviews with face-to-face interviews for those without telephones. This approach depends on the absence of differential mode-effects on the answers obtained or on the ability to account for these effects when they occur.
Release date: 1987-06-15
94. Some aspects of quality of cancer mortality and incidence statistics Archived
Articles and reports: 12-001-X198300114334
Description:
Statistics Canada, Canada’s central statistical agency, has been compiling national mortality statistics, including those on cancer mortality since 1921. Also, cancer incidence data are available from 1969.
The data quality of these files may be assessed in a variety of ways. Ratios of cancer mortality to incidence give some information on coverage errors. Micro-data matches between incidence and mortality files give an indication of misclassifications. As well, multiple registrations for cancer incidence may be duplicates. Completeness and availability of data items are also important for special studies.
In this paper, the feasibility of using these measures of data quality and the implications of these measures are discussed.
Release date: 1983-06-15

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