Quality assurance
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- Surveys and statistical programs – Documentation: 11-522-X20010016225Description:
The European Union Labour Forces Survey (LFS) is based on national surveys that were originally very different. For the past decade, under pressure from increasingly demanding users (particularly with respect to timeliness, comparability and flexibility), the LFS has been subjected to a constant process of quality improvement.
The following topics are presented in this paper:A. the quality improvement process, which comprises screening national survey methods, target structure, legal foundations, quality reports, more accurate and more explicit definitions of components, etc.;B. expected or achieved results, which include an ongoing survey producing quarterly results within reasonable time frames, comparable employment and unemployment rates over time and space in more than 25 countries, specific information on current political topics, etc.;C. continuing shortcomings, such as implementation delays in certain countries, possibilities of longitudinal analysis, public access to microdata, etc.; D. future tasks envisioned, such as adaptation of the list of ISCO and ISCED variables and nomenclatures (to take into account evolution in employment and teaching methods), differential treatment of structural variables and increased recourse to administrative files (to limit respondent burden), harmonization of questionnaires, etc.
Release date: 2002-09-12 - 2. The importance of a quality culture ArchivedArticles and reports: 11-522-X20010016227Description:
The reputation of a national statistical office depends on the level of service it provides. Quality must be a core value and providing excellent service has to be embedded in the culture of a statistical organization.
The paper outlines what is meant by a high quality statistical service. It explores factors that contribute to a quality work culture. In particular, it outlines the activities and experiences of the Australian Bureau of Statistics in maintaining a quality culture.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016228Description:
The Current Population Survey is the primary source of labour force data for the United States. Throughout any survey process, it is critical that data quality be ensured. This paper discusses how quality issues are addressed during all steps of the survey process, including the development of the sample frame, sampling operations, sample control, data collection, editing, imputation, estimation, questionnaire development. It also reviews the quality evaluations that are built into the survey process. The paper concludes with a discussion of current research and possible future improvements to the survey.
Release date: 2002-09-12 - Surveys and statistical programs – Documentation: 11-522-X20010016229Description:
This paper discusses the approach that Statistics Canada has taken to improve the quality of annual business surveys through their integration in the Unified Enterprise Survey (UES). The primary objective of the UES is to measure the final annual sales of goods and services accurately by province, in sufficient detail and in a timely manner.
This paper describes the methodological approaches that the UES has used to improve financial and commodity data quality in four broad areas. These include improved coherence of the data collected from different levels of the enterprise, better coverage of industries, better depth of information (in the sense of more content detail and estimates for more detailed domains) and better consistency of the concepts and methods across industries.
The approach, in achieving quality, has been to (a) establish a base measure of the quality of the business survey program prior to the UES, (b) measure the annual data quality of the UES, and (c) carry out specific studies to better understand the quality of UES data and methods.
Release date: 2002-09-12 - 5. Large and complex surveys - discussion ArchivedArticles and reports: 11-522-X20010016230Description:
This publication consists of three papers, each addressing data quality issues associated with a large and complex survey. Two of the case studies involve household surveys of labour force activity and the third focuses on a business survey. The papers each address a data quality topic from a different perspective, but share some interesting common threads.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016231Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. Its is intended for an audience of survey methodologists.
In 2000, the Behavioral Risk Factor Surveillance System (BRFSS) conducted monthly telephone surveys in 50 American states, the District of Columbia, and Puerto Rico: each was responsible for collecting its own survey data. In Maine, data collection was split between the state health department and ORC Macro, a commercial market research firm. Examination of survey outcome rates, selection biases and missing values for income suggest that the Maine health department data are more accurate. However, out of 18 behavioural health risk factors, only four are statistically different by data collector, and for these four factors, the data collected by ORC Macro seem more accurate.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016235Description:
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.
Police records collected by the Federal Bureau of Investigation (FBI) through the Uniform Crime Reporting (UCR) Program are the leading source of national crime statistics. Recently, audits to correct UCR records have raised concerns as to how to handle the errors discovered in these files. Concerns centre around the methodology used to detect errors and the procedures used to correct errors once they have been discovered. This paper explores these concerns, focusing on sampling methodology, establishment of a statistical-adjustment factor, and alternative solutions. The paper distinguishes the difference between sample adjustment and sample estimates of an agency's data, and recommends sample adjustment as the most accurate way of dealing with errors.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016236Description:
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.
The Uniform Crime Reporting (UCR) Program has devoted a considerable amount of resources in a continuous effort to improve the quality of its data. In this paper, the authors introduce and discuss the use of the cross-ratios and chi-square measures to evaluate the rationality of the data. The UCR data is used to empirically illustrate this approach.
Release date: 2002-09-12 - 9. Data detectives: uncovering systematic errors ArchivedArticles and reports: 11-522-X20010016237Description:
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.
Secondary users of health information often assume that administrative data provides a relatively sound basis for making important planning and policy decisions. If errors are evenly or randomly distributed, this assumption may have little impact on these decisions. However, when information sources contain systematic errors, or when systematic errors are introduced during the creation of master files, this assumption can be damaging.
The most common systematic errors involve underreporting activities for a specific population; inaccurate re-coding of spatial information; and differences in data entry protocols, which have raised questions about the consistency of data submitted by different tracking agencies. The Central East Health Information Partnership (CEHIP) has identified a number of systematic errors in administrative databases and has documented many of these in reports distributed to partner organizations.
This paper describes how some of these errors were identified and notes the processes that give rise to the loss of data integrity. The conclusion addresses some of the impacts these problems have for health planners, program managers and policy makers.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016238Description:
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.
Research programs building on population-based, longitudinal administrative data and record-linkage techniques are found in England, Scotland, the United States (the Mayo Clinic), Western Australia and Canada. These systems can markedly expand both the methodological and the substantive research in health and health care.
This paper summarizes published, Canadian data quality studies regarding registries, hospital discharges, prescription drugs, and physician claims. It makes suggestions for improving registries, facilitating record linkage and expanding research into social epidemiology. New trends in case identification and health status measurement using administrative data have also been noted. And the differing needs for data quality research in each province have been highlighted.
Release date: 2002-09-12
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- 1. The importance of a quality culture ArchivedArticles and reports: 11-522-X20010016227Description:
The reputation of a national statistical office depends on the level of service it provides. Quality must be a core value and providing excellent service has to be embedded in the culture of a statistical organization.
The paper outlines what is meant by a high quality statistical service. It explores factors that contribute to a quality work culture. In particular, it outlines the activities and experiences of the Australian Bureau of Statistics in maintaining a quality culture.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016228Description:
The Current Population Survey is the primary source of labour force data for the United States. Throughout any survey process, it is critical that data quality be ensured. This paper discusses how quality issues are addressed during all steps of the survey process, including the development of the sample frame, sampling operations, sample control, data collection, editing, imputation, estimation, questionnaire development. It also reviews the quality evaluations that are built into the survey process. The paper concludes with a discussion of current research and possible future improvements to the survey.
Release date: 2002-09-12 - 3. Large and complex surveys - discussion ArchivedArticles and reports: 11-522-X20010016230Description:
This publication consists of three papers, each addressing data quality issues associated with a large and complex survey. Two of the case studies involve household surveys of labour force activity and the third focuses on a business survey. The papers each address a data quality topic from a different perspective, but share some interesting common threads.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016231Description:
This paper discusses in detail issues dealing with the technical aspects of designing and conducting surveys. Its is intended for an audience of survey methodologists.
In 2000, the Behavioral Risk Factor Surveillance System (BRFSS) conducted monthly telephone surveys in 50 American states, the District of Columbia, and Puerto Rico: each was responsible for collecting its own survey data. In Maine, data collection was split between the state health department and ORC Macro, a commercial market research firm. Examination of survey outcome rates, selection biases and missing values for income suggest that the Maine health department data are more accurate. However, out of 18 behavioural health risk factors, only four are statistically different by data collector, and for these four factors, the data collected by ORC Macro seem more accurate.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016235Description:
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.
Police records collected by the Federal Bureau of Investigation (FBI) through the Uniform Crime Reporting (UCR) Program are the leading source of national crime statistics. Recently, audits to correct UCR records have raised concerns as to how to handle the errors discovered in these files. Concerns centre around the methodology used to detect errors and the procedures used to correct errors once they have been discovered. This paper explores these concerns, focusing on sampling methodology, establishment of a statistical-adjustment factor, and alternative solutions. The paper distinguishes the difference between sample adjustment and sample estimates of an agency's data, and recommends sample adjustment as the most accurate way of dealing with errors.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016236Description:
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.
The Uniform Crime Reporting (UCR) Program has devoted a considerable amount of resources in a continuous effort to improve the quality of its data. In this paper, the authors introduce and discuss the use of the cross-ratios and chi-square measures to evaluate the rationality of the data. The UCR data is used to empirically illustrate this approach.
Release date: 2002-09-12 - 7. Data detectives: uncovering systematic errors ArchivedArticles and reports: 11-522-X20010016237Description:
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.
Secondary users of health information often assume that administrative data provides a relatively sound basis for making important planning and policy decisions. If errors are evenly or randomly distributed, this assumption may have little impact on these decisions. However, when information sources contain systematic errors, or when systematic errors are introduced during the creation of master files, this assumption can be damaging.
The most common systematic errors involve underreporting activities for a specific population; inaccurate re-coding of spatial information; and differences in data entry protocols, which have raised questions about the consistency of data submitted by different tracking agencies. The Central East Health Information Partnership (CEHIP) has identified a number of systematic errors in administrative databases and has documented many of these in reports distributed to partner organizations.
This paper describes how some of these errors were identified and notes the processes that give rise to the loss of data integrity. The conclusion addresses some of the impacts these problems have for health planners, program managers and policy makers.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016238Description:
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.
Research programs building on population-based, longitudinal administrative data and record-linkage techniques are found in England, Scotland, the United States (the Mayo Clinic), Western Australia and Canada. These systems can markedly expand both the methodological and the substantive research in health and health care.
This paper summarizes published, Canadian data quality studies regarding registries, hospital discharges, prescription drugs, and physician claims. It makes suggestions for improving registries, facilitating record linkage and expanding research into social epidemiology. New trends in case identification and health status measurement using administrative data have also been noted. And the differing needs for data quality research in each province have been highlighted.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016243Description:
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.
Since 1996, the Census Bureau has been creating Web Computerized Self-Administered Questionnaires (CSAQs). These electronic questionnaires have some data quality advantages over paper questionnaires such as the availability of online help; pre-loaded data; the use of interactive edits (which allows respondents to correct their responses as they are entered); and, for establishment surveys, the ability to import data from spreadsheets. This paper provides an overview of the Census Bureau's Web CSAQs. Each of the Web CSAQ design features promoting data quality are explained, as well as the features that impose data quality obstacles. Finally, some recent, empirical, data quality results from both establishment and household surveys are presented.
Release date: 2002-09-12 - Articles and reports: 11-522-X20010016244Description:
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.
Over the past few years, Statistics New Zealand (SNZ) has experienced an increase in the volume of business survey data supplied by e-mail. However, up until now, SNZ has not had the business processes available to support electronic collection in a way that meets both the needs of SNZ and data suppliers. To this end, SNZ has invested a lot of effort over the last year in investigating how best to approach the problems and opportunities presented by electronic data collection. This paper outlines SNZ's plans to move the e-mail supplied data to a secure lodgement facility and the future development of an internet-based data collection system. It also presents a case study of the Monthly Retail Trade Survey data currently supplied by e-mail. This case study illustrates some of the benefits of electronic data, but also examines some of the costs to the organization and the data quality problems encountered. It also highlights the need to consider the data collection methodology within the wider context of the total survey cycle.
Release date: 2002-09-12
Reference (3)
Reference (3) ((3 results))
- Surveys and statistical programs – Documentation: 11-522-X20010016225Description:
The European Union Labour Forces Survey (LFS) is based on national surveys that were originally very different. For the past decade, under pressure from increasingly demanding users (particularly with respect to timeliness, comparability and flexibility), the LFS has been subjected to a constant process of quality improvement.
The following topics are presented in this paper:A. the quality improvement process, which comprises screening national survey methods, target structure, legal foundations, quality reports, more accurate and more explicit definitions of components, etc.;B. expected or achieved results, which include an ongoing survey producing quarterly results within reasonable time frames, comparable employment and unemployment rates over time and space in more than 25 countries, specific information on current political topics, etc.;C. continuing shortcomings, such as implementation delays in certain countries, possibilities of longitudinal analysis, public access to microdata, etc.; D. future tasks envisioned, such as adaptation of the list of ISCO and ISCED variables and nomenclatures (to take into account evolution in employment and teaching methods), differential treatment of structural variables and increased recourse to administrative files (to limit respondent burden), harmonization of questionnaires, etc.
Release date: 2002-09-12 - Surveys and statistical programs – Documentation: 11-522-X20010016229Description:
This paper discusses the approach that Statistics Canada has taken to improve the quality of annual business surveys through their integration in the Unified Enterprise Survey (UES). The primary objective of the UES is to measure the final annual sales of goods and services accurately by province, in sufficient detail and in a timely manner.
This paper describes the methodological approaches that the UES has used to improve financial and commodity data quality in four broad areas. These include improved coherence of the data collected from different levels of the enterprise, better coverage of industries, better depth of information (in the sense of more content detail and estimates for more detailed domains) and better consistency of the concepts and methods across industries.
The approach, in achieving quality, has been to (a) establish a base measure of the quality of the business survey program prior to the UES, (b) measure the annual data quality of the UES, and (c) carry out specific studies to better understand the quality of UES data and methods.
Release date: 2002-09-12 - Surveys and statistical programs – Documentation: 62F0026M2002001Description:
This report describes the quality indicators produced for the 2000 Survey of Household Spending. It covers the usual quality indicators that help users interpret the data, such as coefficients of variation, non-response rates, slippage rates and imputation rates.
Release date: 2002-06-28
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