Quality assurance
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- Articles and reports: 82-003-X201500714205Description:
Discrepancies between self-reported and objectively measured physical activity are well-known. For the purpose of validation, this study compares a new self-reported physical activity questionnaire with an existing one and with accelerometer data.
Release date: 2015-07-15 - Surveys and statistical programs – Documentation: 62F0026M2010004Description:
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 - Surveys and statistical programs – Documentation: 62F0026M2010005Description:
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 - 4. Evaluating the hyperactivity/inattention subscale of the National Longitudinal Survey of Children and Youth ArchivedArticles and reports: 82-003-X201000211234Geography: CanadaDescription:
This article evaluates the parent-reported Hyperactivity/Inattention Subscale of the National Longitudinal Survey of Children and Youth with data from cycle 1 (1994/1995) of the survey.
Release date: 2010-06-16 - Surveys and statistical programs – Documentation: 62F0026M2010002Description:
This report describes the quality indicators produced for the 2005 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: 2010-04-26 - Surveys and statistical programs – Documentation: 62F0026M2010003Description:
This report describes the quality indicators produced for the 2006 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: 2010-04-26 - 7. Quality control and data reduction procedures for accelerometry-derived measures of physical activity ArchivedArticles and reports: 82-003-X201000111066Geography: CanadaDescription:
This article considers critical quality control and data reduction procedures that should be addressed before physical activity information is derived from accelerometry data.
Release date: 2010-01-13 - Articles and reports: 11-522-X200800010976Description:
Many survey organizations use the response rate as an indicator for the quality of survey data. As a consequence, a variety of measures are implemented to reduce non-response or to maintain response at an acceptable level. However, the response rate is not necessarily a good indicator of non-response bias. A higher response rate does not imply smaller non-response bias. What matters is how the composition of the response differs from the composition of the sample as a whole. This paper describes the concept of R-indicators to assess potential differences between the sample and the response. Such indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. Some practical examples are given.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800011002Description:
Based on a representative sample of the Canadian population, this article quantifies the bias resulting from the use of self-reported rather than directly measured height, weight and body mass index (BMI). Associations between BMI categories and selected health conditions are compared to see if the misclassification resulting from the use of self-reported data alters associations between obesity and obesity-related health conditions. The analysis is based on 4,567 respondents to the 2005 Canadian Community Health Survey (CCHS) who, during a face-to-face interview, provided self-reported values for height and weight and were then measured by trained interviewers. Based on self-reported data, a substantial proportion of individuals with excess body weight were erroneously placed in lower BMI categories. This misclassification resulted in elevated associations between overweight/obesity and morbidity.
Release date: 2009-12-03 - Articles and reports: 12-001-X200900110887Description:
Many survey organisations focus on the response rate as being the quality indicator for the impact of non-response bias. As a consequence, they implement a variety of measures to reduce non-response or to maintain response at some acceptable level. However, response rates alone are not good indicators of non-response bias. In general, higher response rates do not imply smaller non-response bias. The literature gives many examples of this (e.g., Groves and Peytcheva 2006, Keeter, Miller, Kohut, Groves and Presser 2000, Schouten 2004).
We introduce a number of concepts and an indicator to assess the similarity between the response and the sample of a survey. Such quality indicators, which we call R-indicators, may serve as counterparts to survey response rates and are primarily directed at evaluating the non-response bias. These indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. We apply the R-indicators to two practical examples.
Release date: 2009-06-22
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- Articles and reports: 82-003-X201500714205Description:
Discrepancies between self-reported and objectively measured physical activity are well-known. For the purpose of validation, this study compares a new self-reported physical activity questionnaire with an existing one and with accelerometer data.
Release date: 2015-07-15 - 2. Evaluating the hyperactivity/inattention subscale of the National Longitudinal Survey of Children and Youth ArchivedArticles and reports: 82-003-X201000211234Geography: CanadaDescription:
This article evaluates the parent-reported Hyperactivity/Inattention Subscale of the National Longitudinal Survey of Children and Youth with data from cycle 1 (1994/1995) of the survey.
Release date: 2010-06-16 - 3. Quality control and data reduction procedures for accelerometry-derived measures of physical activity ArchivedArticles and reports: 82-003-X201000111066Geography: CanadaDescription:
This article considers critical quality control and data reduction procedures that should be addressed before physical activity information is derived from accelerometry data.
Release date: 2010-01-13 - Articles and reports: 11-522-X200800010976Description:
Many survey organizations use the response rate as an indicator for the quality of survey data. As a consequence, a variety of measures are implemented to reduce non-response or to maintain response at an acceptable level. However, the response rate is not necessarily a good indicator of non-response bias. A higher response rate does not imply smaller non-response bias. What matters is how the composition of the response differs from the composition of the sample as a whole. This paper describes the concept of R-indicators to assess potential differences between the sample and the response. Such indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. Some practical examples are given.
Release date: 2009-12-03 - Articles and reports: 11-522-X200800011002Description:
Based on a representative sample of the Canadian population, this article quantifies the bias resulting from the use of self-reported rather than directly measured height, weight and body mass index (BMI). Associations between BMI categories and selected health conditions are compared to see if the misclassification resulting from the use of self-reported data alters associations between obesity and obesity-related health conditions. The analysis is based on 4,567 respondents to the 2005 Canadian Community Health Survey (CCHS) who, during a face-to-face interview, provided self-reported values for height and weight and were then measured by trained interviewers. Based on self-reported data, a substantial proportion of individuals with excess body weight were erroneously placed in lower BMI categories. This misclassification resulted in elevated associations between overweight/obesity and morbidity.
Release date: 2009-12-03 - Articles and reports: 12-001-X200900110887Description:
Many survey organisations focus on the response rate as being the quality indicator for the impact of non-response bias. As a consequence, they implement a variety of measures to reduce non-response or to maintain response at some acceptable level. However, response rates alone are not good indicators of non-response bias. In general, higher response rates do not imply smaller non-response bias. The literature gives many examples of this (e.g., Groves and Peytcheva 2006, Keeter, Miller, Kohut, Groves and Presser 2000, Schouten 2004).
We introduce a number of concepts and an indicator to assess the similarity between the response and the sample of a survey. Such quality indicators, which we call R-indicators, may serve as counterparts to survey response rates and are primarily directed at evaluating the non-response bias. These indicators may facilitate analysis of survey response over time, between various fieldwork strategies or data collection modes. We apply the R-indicators to two practical examples.
Release date: 2009-06-22 - 7. The feasibility of establishing correction factors to adjust self-reported estimates of obesity ArchivedArticles and reports: 82-003-X200800310680Geography: CanadaDescription:
This study examines the feasibility of developing correction factors to adjust self-reported measures of body mass index to more closely approximate measured values. Data are from the 2005 Canadian Community Health Survey, in which respondents were asked to report their height and weight, and were subsequently measured.
Release date: 2008-09-17 - Articles and reports: 11-522-X20050019434Description:
Traditional methods for statistical disclosure limitation in tabular data are cell suppression, data rounding and data perturbation. Because the suppression mechanism is not describable in probabilistic terms, suppressed tables are not amenable to statistical methods such as imputation. Data quality characteristics of suppressed tables are consequently poor.
Release date: 2007-03-02 - 9. Simulation study to assess the precision of the two-stage cluster survey for injection safety ArchivedArticles and reports: 11-522-X20020016721Description:
This paper examines the simulation study that was conducted to assess the sampling scheme designed for the World Health Organization (WHO) Injection Safety Assessment Survey. The objective of this assessment survey is to determine whether facilities in which injections are given meet the necessary safety requirements for injection administration, equipment, supplies and waste disposal. The main parameter of interest is the proportion of health care facilities in a country that have safe injection practices.
The objective of this simulation study was to assess the accuracy and precision of the proposed sampling design. To this end, two artificial populations were created based on the two African countries of Niger and Burkina Faso, in which the pilot survey was tested. To create a wide variety of hypothetical populations, the assignment of whether a health care facility was safe or not was based on the different combinations of the population proportion of safe health care facilities in the country, the homogeneity of the districts in the country with respect to injection safety, and whether the health care facility was located in an urban or rural district.
Using the results of the simulation, a multi-factor analysis of variance was used to determine which factors affect the outcome measures of absolute bias, standard error and mean-squared error.
Release date: 2004-09-13 - Articles and reports: 62F0014M2004017Geography: CanadaDescription:
This paper documents the approach used to construct the shelter element of the current spatial index program. The intercity indexes of the retail price differentials program of Prices Division had, until recently, excluded any reference to shelter because of conceptual issues. A rental equivalence approach is used for measuring spatial variations in the costs of shelter services among cities. To control for quality variations across areas, a semi-log separate hedonic regression methodology is used to construct the Laspeyres, Paasche, and Fisher Törnqvist interarea indices.
Release date: 2004-04-16
Reference (15)
Reference (15) (0 to 10 of 15 results)
- Surveys and statistical programs – Documentation: 62F0026M2010004Description:
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 - Surveys and statistical programs – Documentation: 62F0026M2010005Description:
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 - Surveys and statistical programs – Documentation: 62F0026M2010002Description:
This report describes the quality indicators produced for the 2005 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: 2010-04-26 - Surveys and statistical programs – Documentation: 62F0026M2010003Description:
This report describes the quality indicators produced for the 2006 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: 2010-04-26 - 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 - 6. Combining census, survey, demographic and administrative data to produce a one number census ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015638Description:
The focus of Symposium'99 is on techniques and methods for combining data from different sources and on analysis of the resulting data sets. In this talk we illustrate the usefulness of taking such an "integrating" approach when tackling a complex statistical problem. The problem itself is easily described - it is how to approximate, as closely as possible, a "perfect census", and in particular, how to obtain census counts that are "free" of underenumeration. Typically, underenumeration is estimated by carrying out a post enumeration survey (PES) following the census. In the UK in 1991 the PEF failed to identify the full size of the underenumeration and so demographic methods were used to estimate the extent of the undercount. The problems with the "traditional" PES approach in 1991 resulted in a joint research project between the Office for National Statistics and the Department of Social Statistics at the University of Southampton aimed at developing a methodology which will allow a "One Number Census" in the UK in 2001. That is, underenumeration will be accounted for not just at high levels of aggregation, but right down to the lowest levels at which census tabulations are produced. In this way all census outputs will be internally consistent, adding to the national population estimates. The basis of this methodology is the integration of information from a number of data sources in order to achieve this "One Number".
Release date: 2000-03-02 - 7. Creation of an occupational surveillance system in Canada: Combining data for a unique Canadian study ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015652Description:
Objective: To create an occupational surveillance system by collecting, linking, evaluating and disseminating data relating to occupation and mortality with the ultimate aim of reducing or preventing excess risk among workers and the general population.
Release date: 2000-03-02 - 8. A comparison of two record linkage procedures ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015664Description:
Much work on probabilistic methods of linkage can be found in the statistical literature. However, although many groups undoubtedly still use deterministic procedures, not much literature is available on these strategies. Furthermore there appears to exist no documentation on the comparison of results for the two strategies. Such a comparison is pertinent in the situation where we have only non-unique identifiers like names, sex, race etc. as common identifiers on which the databases are to be linked. In this work we compare a stepwise deterministic linkage strategy with the probabilistic strategy, as implemented in AUTOMATCH, for such a situation. The comparison was carried out on a linkage between medical records from the Regional Perinatal Intensive Care Centers database and education records from the Florida Department of Education. Social security numbers, available in both databases, were used to decide the true status of the record pair after matching. Match rates and error rates for the two strategies are compared and a discussion of their similarities and differences, strengths and weaknesses is presented.
Release date: 2000-03-02 - 9. A donor imputation system to create a census database fully adjusted for underenumeration ArchivedSurveys and statistical programs – Documentation: 11-522-X19990015668Description:
Following the problems with estimating underenumeration in the 1991 Census of England and Wales the aim for the 2001 Census is to create a database that is fully adjusted to net underenumeration. To achieve this, the paper investigates weighted donor imputation methodology that utilises information from both the census and census coverage survey (CCS). The US Census Bureau has considered a similar approach for their 2000 Census (see Isaki et al 1998). The proposed procedure distinguishes between individuals who are not counted by the census because their household is missed and those who are missed in counted households. Census data is linked to data from the CCS. Multinomial logistic regression is used to estimate the probabilities that households are missed by the census and the probabilities that individuals are missed in counted households. Household and individual coverage weights are constructed from the estimated probabilities and these feed into the donor imputation procedure.
Release date: 2000-03-02 - Surveys and statistical programs – Documentation: 11-522-X19990015680Description:
To augment the amount of available information, data from different sources are increasingly being combined. These databases are often combined using record linkage methods. When there is no unique identifier, a probabilistic linkage is used. In that case, a record on a first file is associated with a probability that is linked to a record on a second file, and then a decision is taken on whether a possible link is a true link or not. This usually requires a non-negligible amount of manual resolution. It might then be legitimate to evaluate if manual resolution can be reduced or even eliminated. This issue is addressed in this paper where one tries to produce an estimate of a total (or a mean) of one population, when using a sample selected from another population linked somehow to the first population. In other words, having two populations linked through probabilistic record linkage, we try to avoid any decision concerning the validity of links and still be able to produce an unbiased estimate for a total of the one of two populations. To achieve this goal, we suggest the use of the Generalised Weight Share Method (GWSM) described by Lavallée (1995).
Release date: 2000-03-02
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