Quality assurance

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All (250) (0 to 10 of 250 results)

1. Income Research Paper Series
Journals and periodicals: 75F0002M
Description: This series provides detailed documentation on income developments, including survey design issues, data quality evaluation and exploratory research.
Release date: 2024-02-22
2. 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
3. Distributions of Household Economic Accounts, estimates of asset, liability and net worth distributions, 2010 to 2023, technical methodology and quality report
Articles and reports: 13-604-M2024001
Description: This documentation outlines the methodology used to develop the Distributions of household economic accounts published in January 2024 for the reference years 2010 to 2023. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.
Release date: 2024-01-22
4. Distributions of Household Economic Accounts, estimates of asset, liability and net worth distributions, 2010 to 2022, technical methodology and quality report
Articles and reports: 13-604-M2023001
Description: This documentation outlines the methodology used to develop the Distributions of household economic accounts published in March 2023 for the reference years 2010 to 2022. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.
Release date: 2023-03-31
5. Distributions of Household Economic Accounts, estimates of asset, liability and net worth distributions, 2010 to 2021, technical methodology and quality report
Articles and reports: 13-604-M2022002
Description:
This documentation outlines the methodology used to develop the Distributions of household economic accounts published in August 2022 for the reference years 2010 to 2021. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.

Release date: 2022-08-03
6. The Importance of Data Quality
19-22-0009
Description:
Join us as Statistics Canada’s Quality Secretariat will give a presentation on the importance of data quality. We are living in an exciting time for data: sources are more abundant, they are being generated in innovative ways, and they are available quicker than ever. However, a data source is not only worthless if it does not meet basic quality standards – it can be misleading, and worse than having no data at all! Statistics Canada’s Quality Secretariat has a mandate to promote good quality practices within the agency, across the Government of Canada, and internationally. For quality to truly be present, it must be incorporated into each process (from design to analysis) and into the product itself – whether that product is a microdata file or estimates derived from it. We will address why data quality is important and how one can evaluate it in practice. We will cover some basic concepts in data quality (quality assurance vs. control, metadata, etc.), and present data quality as a multidimensional concept. Finally, we will show data quality in action by evaluating a data source together. All data quality literacy levels are welcome. After all, everybody plays a part in quality!

https://www.statcan.gc.ca/en/services/webinars/19220009

Release date: 2022-01-26
7. Creation of a composite quality indicator for administrative data-based estimates using clustering Archived
Articles and reports: 11-522-X202100100015
Description: National statistical agencies such as Statistics Canada have a responsibility to convey the quality of statistical information to users. The methods traditionally used to do this are based on measures of sampling error. As a result, they are not adapted to the estimates produced using administrative data, for which the main sources of error are not due to sampling. A more suitable approach to reporting the quality of estimates presented in a multidimensional table is described in this paper. Quality indicators were derived for various post-acquisition processing steps, such as linkage, geocoding and imputation, by estimation domain. A clustering algorithm was then used to combine domains with similar quality levels for a given estimate. Ratings to inform users of the relative quality of estimates across domains were assigned to the groups created. This indicator, called the composite quality indicator (CQI), was developed and experimented with in the Canadian Housing Statistics Program (CHSP), which aims to produce official statistics on the residential housing sector in Canada using multiple administrative data sources.
Keywords: Unsupervised machine learning, quality assurance, administrative data, data integration, clustering.
Release date: 2021-10-22
8. Empowering analysts to consider the ethics of their work: A case study of the UK Statistics Authority's data ethics framework Archived
Articles and reports: 11-522-X202100100023
Description:
Our increasingly digital society provides multiple opportunities to maximise our use of data for the public good – using a range of sources, data types and technologies to enable us to better inform the public about social and economic matters and contribute to the effective development and evaluation of public policy. Ensuring use of data in ethically appropriate ways is an important enabler for realising the potential to use data for public good research and statistics. Earlier this year the UK Statistics Authority launched the Centre for Applied Data Ethics to provide applied data ethics services, advice, training and guidance to the analytical community across the United Kingdom. The Centre has developed a framework and portfolio of services to empower analysts to consider the ethics of their research quickly and easily, at the research design phase thus promoting a culture of ethics by design. This paper will provide an overview of this framework, the accompanying user support services and the impact of this work.

Key words: Data ethics, data, research and statistics

Release date: 2021-10-22
9. Distributions of Household Economic Accounts, estimates of asset, liability and net worth distributions, 2010 to 2020, technical methodology and quality report
Articles and reports: 13-604-M2021001
Description:
This documentation outlines the methodology used to develop the Distributions of household economic accounts published in September 2021 for the reference years 2010 to 2020. It describes the framework and the steps implemented to produce distributional information aligned with the National Balance Sheet Accounts and other national accounts concepts. It also includes a report on the quality of the estimated distributions.
Release date: 2021-09-07
10. 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

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Analysis (171)

Analysis (171) (160 to 170 of 171 results)

161. Instrumental variable estimation of gross flows in the presence of measurement error Archived
Articles and reports: 12-001-X19970013105
Description:
The problem of estimating transition rates from longitudinal survey data in the presence of misclassification error is considered. Approaches which use external information on misclassification rates are reviewed, together with alternative models for measurement error. We define categorical instrumental variables and propose methods for the identification and estimation of models including such variables by viewing the model as a restricted latent class model. The numerical properties of the implied instrumental variable estimators of flow rates are studied using data from the Panel Study of Income Dynamics.
Release date: 1997-08-18
162. Project on Matching Census 1986 Database and Manitoba Health Care Files: Private Households Component Archived
Articles and reports: 11F0019M1996091
Geography: Province or territory
Description:
Introduction: In the current economic context, all partners in health care delivery systems, be they public or private, are obliged to identify the factors that influence the utilization of health care services. To improve our understanding of the phenomena that underlie these relationships, Statistics Canada and the Manitoba Centre for Health Policy and Evaluation have just set up a new database. For a representative sample of the population of the province of Manitoba, cross-sectional microdata on individuals' health and socio-economic characteristics were linked with detailed longitudinal data on utilization of health care services.
Data and methods: The 1986-87 Health and Activity Limitation Survey, the 1986 Census and the files of Manitoba Health were matched (without using names or addresses) by means of the CANLINK software. In the pilot project, 20,000 units were selected from the Census according to modern sampling techniques. Before the files were matched, consultations were held and an agreement was signed by all parties in order to establish a framework for protecting privacy and preserving the confidentiality of the data.
Results: A matching rate of 74% was obtained for private households. A quality evaluation based on the comparisons of names and addresses over a small subsample established that the overall concordance rate among matched pairs was 95.5%. The match rates and concordance rates varied according to age and household composition. Estimates produced from the sample accurately reflected the socio-demographic profile, mortality, hospitalization rate, health care costs and consumption of health care by Manitoba residents.
Discussion: The matching rate of 74% was satisfactory in comparison with the response rates reported in most population surveys. Because of the excellent concordance rate and the accuracy of the estimates obtained from the sample, this database will provide an adequate basis for studying the association between socio-demographic characteristics, health and health care utilization in province of Manitoba.
Release date: 1996-03-30
163. Matrix masking methods for disclosure limitation in microdata Archived
Articles and reports: 12-001-X199400214420
Description:
The statistical literature contains many methods for disclosure limitation in microdata. However, their use by statistical agencies and understanding of their properties and effects has been limited. For purposes of furthering research and use of these methods, and facilitating their evaluation and quality assurance, it would be desirable to formulate them within a single framework. A framework called matrix masking - based on ordinary matrix arithmetic - is presented, and explicit matrix mask formulations are given for the principal microdata disclosure limitation methods in current use. This enables improved understanding and implementation of these methods by statistical agencies and other practitioners.
Release date: 1994-12-15
164. Optimum two-stage sample design for ratio estimators: Application to quality control - 1990 French census Archived
Articles and reports: 12-001-X199300214456
Description:
This study is based on the use of superpopulation models to anticipate, before data collection, the variance of a measure by ratio sampling. The method, based on models that are both simple and fairly realistic, produces expressions of varying complexity and then optimizes them, in some cases rigorously, in others approximately. The solution to the final problem discussed points up a rarely considered factor in sample design optimization: the cost related to collecting individual information.
Release date: 1993-12-15
165. Job ads: A leading indicator? Archived
Articles and reports: 75-001-X19890032282
Geography: Canada
Description:
The Help-wanted Index measures job ads as an indicator of labour demand. The index is considered a leading indicator of labour market conditions and of general economic activity. This study looks at the performance of the index during the last three business cycles.
Release date: 1989-09-30
166. Automated quality assurance processing of administrative record files Archived
Articles and reports: 12-001-X198900114573
Description:
The Census Bureau makes extensive use of administrative records information in its various economic programs. Although the volume of records processed annually is vast, even larger numbers will be received during the census years. Census Bureau mainframe computers perform quality control (QC) tabulations on the data; however, since such a large number of QC tables are needed and resources for programming are limited and costly, a comprehensive mainframe QC system is difficult to attain. Add to this the sensitive nature of the data and the potentially very negative ramifications from erroneous data, and the need becomes quite apparent for a sophisticated quality assurance system on the microcomputer level. Such a system is being developed by the Economic Surveys Division and will be in place for the 1987 administrative records data files. The automated quality assurance system integrates micro and mainframe computer technology. Administrative records data are received weekly and processed initially through mainframe QC programs. The mainframe output is transferred to a microcomputer and formatted specifically for importation to a spreadsheet program. Systematic quality verification occurs within the spreadsheet structure, as data review, error detection, and report generation are accomplished automatically. As a result of shifting processes from mainframe to microcomputer environments, the system eases the burden on the programming staff, increases the flexibility of the analytical staff, and reduces processing costs on the mainframe and provides the comprehensive quality assurance component for administrative records.
Release date: 1989-06-15
167. Quality assurance sampling for evaluating health parameters in developing countries Archived
Articles and reports: 12-001-X198900114576
Description:
A typical goal of health workers in the developing world is to ascertain whether or not a population meets certain standards, such as the proportion vaccinated against a certain disease. Because populations tend to be large, and resources and time available for studies limited, it is usually necessary to select a sample from the population and then make estimates regarding the entire population. Depending upon the proportion of the sample individuals who were not vaccinated, a decision will be made as to whether the coverage is adequate or whether additional efforts must be initiated to improve coverage in the population. Several sampling methods are currently in use. Among these is a modified method of cluster sampling recommended by the Expanded Programme on Immunization (EPI) of the World Health Organization. More recently, quality assurance sampling (QAS), a method commonly used for inspecting manufactured products, has been proposed as a potentially useful method for continually monitoring health service programs. In this paper, the QAS method is described and an example of how this type of sampling might be used is provided.
Release date: 1989-06-15
168. Quality control processing system for survey operations Archived
Articles and reports: 12-001-X198800214585
Description:
The methods used to control the quality of Statistics Canada’s survey processing operations generally involve acceptance sampling by attributes with rectifying inspection, contained within the broader framework of Acceptance Control. Although these methods are recognized as good corrective procedures, they do little in themselves to prevent errors from recurring. As this is of the utmost importance in any quality program, the Quality Control Processing System (QCPS) has been designed with error prevention as one of its primary focuses. Accordingly, the system produces feedback reports and graphs for operators, supervisors and managers involved in the various operations. The system also produces information concerning changes in the inspection environments which enable methodologists to adjust inspection plans/procedures in accordance with the strategy of Acceptance Control. This paper highlights the main tabulation and estimation features of the QCPS and the manner in which it serves to support the principal quality control programs at Statistics Canada. Major capabilities from a methodological and systems perspective are discussed.
Release date: 1988-12-15
169. The use of matching in the evaluation of non-sampling errors in the 1981 Canadian Census of Agriculture Archived
Articles and reports: 12-001-X198400214356
Description:
This paper discusses the use of matching between files of comparable data in the evaluation of non-sampling error. As an example of the technique, the data quality evaluation of the 1981 Canadian Census of Agriculture is described and some results presented.
Release date: 1984-12-14
170. 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 (78)

Reference (78) (0 to 10 of 78 results)

1. 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
2. Statistics Canada Quality Guidelines
Surveys and statistical programs – Documentation: 12-539-X
Description:
This document brings together guidelines and checklists on many issues that need to be considered in the pursuit of quality objectives in the execution of statistical activities. Its focus is on how to assure quality through effective and appropriate design or redesign of a statistical project or program from inception through to data evaluation, dissemination and documentation. These guidelines draw on the collective knowledge and experience of many Statistics Canada employees. It is expected that Quality Guidelines will be useful to staff engaged in the planning and design of surveys and other statistical projects, as well as to those who evaluate and analyze the outputs of these projects.
Release date: 2019-12-04
3. Data Quality Toolkit
Surveys and statistical programs – Documentation: 12-606-X
Description:
This is a toolkit intended to aid data producers and data users external to Statistics Canada.
Release date: 2017-09-27
4. Comparison of Place of Residence between the T1 Family File and the Census: Evaluation using record linkage Archived
Surveys and statistical programs – Documentation: 91F0015M2017013
Description:
Using records linkage, this article compares the place of residence in the 2011 Census to that of the 2010 T1 Family File (T1FF). The main result is that although the overall level of consistency in the place of residence is relatively high, it decreases, sometimes substantially, for some segments of the population.
Release date: 2017-09-26
5. Statistics Canada's Quality Assurance Framework
Surveys and statistical programs – Documentation: 12-586-X
Description:
The Quality Assurance Framework (QAF) serves as the highest-level governance tool for quality management at Statistics Canada. The QAF gives an overview of the quality management and risk mitigation strategies used by the Agency’s program areas. The QAF is used in conjunction with Statistics Canada management practices, such as those described in the Quality Guidelines.
Release date: 2017-04-21
6. Challenges and results in using Audit trail data to monitor Labour Force Survey data quality Archived
Surveys and statistical programs – Documentation: 11-522-X201700014707
Description:
The Labour Force Survey (LFS) is a monthly household survey of about 56,000 households that provides information on the Canadian labour market. Audit Trail is a Blaise programming option, for surveys like LFS with Computer Assisted Interviewing (CAI), which creates files containing every keystroke and edit and timestamp of every data collection attempt on all households. Combining such a large survey with such a complete source of paradata opens the door to in-depth data quality analysis but also quickly leads to Big Data challenges. How can meaningful information be extracted from this large set of keystrokes and timestamps? How can it help assess the quality of LFS data collection? The presentation will describe some of the challenges that were encountered, solutions that were used to address them, and results of the analysis on data quality.
Release date: 2016-03-24
7. Comparing Survey Data to Administrative Sources: Immigration, Labour, and Demographic data from the Longitudinal and International Study of Adults Archived
Surveys and statistical programs – Documentation: 11-522-X201700014716
Description:
Administrative data, depending on its source and original purpose, can be considered a more reliable source of information than survey-collected data. It does not require a respondent to be present and understand question wording, and it is not limited by the respondent’s ability to recall events retrospectively. This paper compares selected survey data, such as demographic variables, from the Longitudinal and International Study of Adults (LISA) to various administrative sources for which LISA has linkage agreements in place. The agreement between data sources, and some factors that might affect it, are analyzed for various aspects of the survey.
Release date: 2016-03-24
8. Student Pathways and Graduate Outcomes Archived
Surveys and statistical programs – Documentation: 11-522-X201700014717
Description:
Files with linked data from the Statistics Canada, Postsecondary Student Information System (PSIS) and tax data can be used to examine the trajectories of students who pursue postsecondary education (PSE) programs and their post-schooling labour market outcomes. On one hand, administrative data on students linked longitudinally can provide aggregate information on student pathways during postsecondary studies such as persistence rates, graduation rates, mobility, etc. On the other hand, the tax data could supplement the PSIS data to provide information on employment outcomes such as average and median earnings or earnings progress by employment sector (industry), field of study, education level and/or other demographic information, year over year after graduation. Two longitudinal pilot studies have been done using administrative data on postsecondary students of Maritimes institutions which have been longitudinally linked and linked to Statistics Canada Ttx data (the T1 Family File) for relevant years. This article first focuses on the quality of information in the administrative data and the methodology used to conduct these longitudinal studies and derive indicators. Second, it will focus on some limitations when using administrative data, rather than a survey, to define some concepts.
Release date: 2016-03-24
9. Using data linkage to evaluate the consistency of place of residence between census data and tax data Archived
Surveys and statistical programs – Documentation: 11-522-X201700014725
Description:
Tax data are being used more and more to measure and analyze the population and its characteristics. One of the issues raised by the growing use of these type of data relates to the definition of the concept of place of residence. While the census uses the traditional concept of place of residence, tax data provide information based on the mailing address of tax filers. Using record linkage between the census, the National Household Survey and tax data from the T1 Family File, this study examines the consistency level of the place of residence of these two sources and its associated characteristics.
Release date: 2016-03-24
10. Estimating internal migration: Issues related to using tax data Archived
Surveys and statistical programs – Documentation: 11-522-X201700014726
Description:
Internal migration is one of the components of population growth estimated at Statistics Canada. It is estimated by comparing individuals’ addresses at the beginning and end of a given period. The Canada Child Tax Benefit and T1 Family File are the primary data sources used. Address quality and coverage of more mobile subpopulations are crucial to producing high-quality estimates. The purpose of this article is to present the results of evaluations of these elements using access to more tax data sources at Statistics Canada.
Release date: 2016-03-24

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Date modified:: 2024-04-16