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Cited by 27Survey Sampling and Estimation TechniquesStatistical Methods in EpidemiologySurvey Methodology and Nonresponse

Survey research methods in evaluation and case-control studies

Kalton, Graham, Piesse, Andrea·2007·Statistics in Medicine
DOI 10.1002/sim.2796
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Abstract

Survey research methods are widely used in two types of analytic studies: evaluation studies that measure the effects of interventions; and population‐based case–control studies that investigate the effects of various risk factors on the presence of disease. This paper provides a broad overview of some design and analysis issues related to such studies, illustrated with examples. The lack of random assignment to treatment and control groups in many evaluation studies makes controlling for confounders critically important. Confounder control can be achieved by matching in the design and by various alternative methods in the analysis. One popular analytic method of controlling for confounders is propensity scoring, which bears a close resemblance to survey weighting. The use of population‐based controls has become common in case–control studies. For reasons of cost, population‐based controls are often identified by telephone surveys using random digit dialling (RDD) sampling methods. However, RDD surveys are now experiencing serious problems with response rates. A recent alternative approach is to select controls from frames such as driver license lists that contain valuable demographic information for use in matching. Methods of analysis developed in the survey sampling literature are applicable, at least to some degree, in the analyses of evaluation and population‐based case–control studies. In particular, the effects of complex sample designs can be taken into account using survey sampling variance estimation methods. Several survey analysis software packages are available for carrying out the computations. Copyright © 2007 John Wiley & Sons, Ltd.

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  • Survey research methods with inverse participation probability weights were used to fit logistic regression models.

    “To ensure that the results represented the study base, we used survey research methods to fi t the logistic regression models, with participants being assigned weights equal to the inverse of the estimated participation probability in strata de fi ned by the entry case group and demographic factors (38).”

    From Maternal Intake of Supplemental Iron and Risk of Autism Spectrum Disorder (2014) · cites this paper as [38]

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Authors
Kalton, G., & Piesse, A.
Affiliations
Westat (United States) (US)
Corresponding author
Kalton, Graham
ORCID
Venue
Statistics in Medicine
Publisher
Wiley
Published
2007-02-05
Volume
26
Issue
8
Pages
1675-1687
ISSN
  • 0277-6715 (ISSN-L)
  • 1097-0258
DOI
10.1002/sim.2796
OpenAlex
W2113961526
Cited by
27
References
44
Citations by year
2022: 1 · 2021: 2 · 2019: 1 · 2016: 3 · 2014: 4 · 2013: 4 · 2012: 4
FWCI
1.58
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
  • Statistics in Medicine (publishedVersion)
  • PubMed (publishedVersion)
Topics
  • Physical Sciences › Mathematics › Statistics and Probability › Survey Sampling and Estimation Techniques
  • Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Epidemiology
  • Social Sciences › Sociology and Political Science › Survey Methodology and Nonresponse
Keywords
survey methodology, evaluation research, case-control study, confounder control, matching, propensity scoring, survey weighting, population-based controls, response rate, complex sampling designs
MeSH terms
Adult, Aged, Data Collection, Data Interpretation, Statistical, Evaluation Studies as Topic, Female, Humans, Male, Middle Aged, United States, Bias, Case-Control Studies

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