Results
All (4)
All (4) ((4 results))
- Articles and reports: 11-522-X200600110415Description:
We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.
Release date: 2008-03-17 - 2. Population-based case control studies ArchivedArticles and reports: 12-001-X20060029546Description:
We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.
Release date: 2006-12-21 - Articles and reports: 11-522-X20010016276Description:
In surveys where interviewers need a high degree of specialist knowledge and training, one is often forced to make do with a small number of highly trained people, each having a high case load. It is well known that this can lead to interviewer variability having a relatively large impact on the total error, particularly for estimates of simple quantities such as means and proportions. In a previous paper (Davis and Scott, 1995) the impact for continuous responses was looked at using a linear components of variance model. However, most responses in health questionnaires are binary and it is known that this approach results in underestimating the intra-cluster and intra-interviewer correlations for binary responses. In this paper,a multi-level binary model is used to explore the impact of interviewer variability on estimated proportions.
Release date: 2002-09-12 - Articles and reports: 12-001-X199500214405Description:
In this paper we explore the effect of interviewer variability on the precision of estimated contrasts between domain means. In the first part we develop a correlated components of variance model to identify the factors that determine the size of the effect. This has implications for sample design and for interviewer training. In the second part we report on an empirical study using data from a large multi-stage survey on dental health. Gender of respondent and ethnic affiliation are used to establish two sets of domains for the comparisons. Overall interviewer and cluster effects make little difference to the variance of male/female comparisons, but there is noticeable increase in the variance of some contrasts between the two ethnic groupings used in this study. Indeed, the impact of interviewer effects for the ethnic comparision is two or three times higher than it is for gender contrasts. These findings have particular relevance for health surveys where it is common to use a small cadre of highly-trained interviewers.
Release date: 1995-12-15
Stats in brief (0)
Stats in brief (0) (0 results)
No content available at this time.
Articles and reports (4)
Articles and reports (4) ((4 results))
- Articles and reports: 11-522-X200600110415Description:
We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.
Release date: 2008-03-17 - 2. Population-based case control studies ArchivedArticles and reports: 12-001-X20060029546Description:
We discuss methods for the analysis of case-control studies in which the controls are drawn using a complex sample survey. The most straightforward method is the standard survey approach based on weighted versions of population estimating equations. We also look at more efficient methods and compare their robustness to model mis-specification in simple cases. Case-control family studies, where the within-cluster structure is of interest in its own right, are also discussed briefly.
Release date: 2006-12-21 - Articles and reports: 11-522-X20010016276Description:
In surveys where interviewers need a high degree of specialist knowledge and training, one is often forced to make do with a small number of highly trained people, each having a high case load. It is well known that this can lead to interviewer variability having a relatively large impact on the total error, particularly for estimates of simple quantities such as means and proportions. In a previous paper (Davis and Scott, 1995) the impact for continuous responses was looked at using a linear components of variance model. However, most responses in health questionnaires are binary and it is known that this approach results in underestimating the intra-cluster and intra-interviewer correlations for binary responses. In this paper,a multi-level binary model is used to explore the impact of interviewer variability on estimated proportions.
Release date: 2002-09-12 - Articles and reports: 12-001-X199500214405Description:
In this paper we explore the effect of interviewer variability on the precision of estimated contrasts between domain means. In the first part we develop a correlated components of variance model to identify the factors that determine the size of the effect. This has implications for sample design and for interviewer training. In the second part we report on an empirical study using data from a large multi-stage survey on dental health. Gender of respondent and ethnic affiliation are used to establish two sets of domains for the comparisons. Overall interviewer and cluster effects make little difference to the variance of male/female comparisons, but there is noticeable increase in the variance of some contrasts between the two ethnic groupings used in this study. Indeed, the impact of interviewer effects for the ethnic comparision is two or three times higher than it is for gender contrasts. These findings have particular relevance for health surveys where it is common to use a small cadre of highly-trained interviewers.
Release date: 1995-12-15
Journals and periodicals (0)
Journals and periodicals (0) (0 results)
No content available at this time.
- Date modified: