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Erschienen in: Translational Behavioral Medicine 2/2016

03.02.2016 | Practice and Public Health Policies

Statistical methodologies to pool across multiple intervention studies

verfasst von: Shrikant I. Bangdiwala, Alok Bhargava, Daniel P. O’Connor, Thomas N. Robinson, Susan Michie, David M. Murray, June Stevens, Steven H. Belle, Thomas N. Templin, Charlotte A. Pratt

Erschienen in: Translational Behavioral Medicine | Ausgabe 2/2016

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Abstract

Combining and analyzing data from heterogeneous randomized controlled trials of complex multiple-component intervention studies, or discussing them in a systematic review, is not straightforward. The present article describes certain issues to be considered when combining data across studies, based on discussions in an NIH-sponsored workshop on pooling issues across studies in consortia (see Belle et al. in Psychol Aging, 18(3):396–405, 2003). Several statistical methodologies are described and their advantages and limitations are explored. Whether weighting the different studies data differently, or via employing random effects, one must recognize that different pooling methodologies may yield different results. Pooling can be used for comprehensive exploratory analyses of data from RCTs and should not be viewed as replacing the standard analysis plan for each study. Pooling may help to identify intervention components that may be more effective especially for subsets of participants with certain behavioral characteristics. Pooling, when supported by statistical tests, can allow exploratory investigation of potential hypotheses and for the design of future interventions.
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Metadaten
Titel
Statistical methodologies to pool across multiple intervention studies
verfasst von
Shrikant I. Bangdiwala
Alok Bhargava
Daniel P. O’Connor
Thomas N. Robinson
Susan Michie
David M. Murray
June Stevens
Steven H. Belle
Thomas N. Templin
Charlotte A. Pratt
Publikationsdatum
03.02.2016
Verlag
Springer US
Erschienen in
Translational Behavioral Medicine / Ausgabe 2/2016
Print ISSN: 1869-6716
Elektronische ISSN: 1613-9860
DOI
https://doi.org/10.1007/s13142-016-0386-8

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