2012
DOI: 10.2105/ajph.2011.300398
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Use of Design Effects and Sample Weights in Complex Health Survey Data: A Review of Published Articles Using Data From 3 Commonly Used Adolescent Health Surveys

Abstract: Given the statistical bias that occurs when design effects of complex data are not incorporated or sample weights are omitted, this study calls for improvement in the dissemination of research findings based on complex sample data. Authors, editors, and reviewers need to work together to improve the transparency of published findings using complex sample data.

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Cited by 79 publications
(63 citation statements)
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“…Because the Add Health data were collected using a complex survey design (described above), we estimate all models using the SAS SurveyLogistic Procedure (An 2002) to obtain appropriate estimates and standard errors (Bell et al 2012). The survey logistic procedure is similar to traditional logistic regression, except for the handling of the variance.…”
Section: Methodsmentioning
confidence: 99%
“…Because the Add Health data were collected using a complex survey design (described above), we estimate all models using the SAS SurveyLogistic Procedure (An 2002) to obtain appropriate estimates and standard errors (Bell et al 2012). The survey logistic procedure is similar to traditional logistic regression, except for the handling of the variance.…”
Section: Methodsmentioning
confidence: 99%
“…35 Following the recommendations of CDC and recent research on use of pooled YRBS data, we used the complex survey procedures in SPSS to take into account the complex sampling design and included sample weights in all of our analyses. 33,36 In particular, in computing standard errors, we used Taylor series linearization.…”
Section: Analytic Planmentioning
confidence: 99%
“…Primary health research involving complex sampling often employs inappropriate statistical approaches to inference, and often gives insufficient detail to provide methodological clarity [1, 2]. Related to this is the issue in repeated cross-sectional studies whereby pooled cross-sectional estimation in the presence of repeat responses from the same individuals can yield biased estimates and incorrect estimates of standard error if inappropriate statistical methodology is applied [2, 3].…”
Section: Introductionmentioning
confidence: 99%