Document Detail


A simple method to correct for the design effect in systematic reviews of trials using paired dichotomous data.
MedLine Citation:
PMID:  17689815     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
BACKGROUND AND OBJECTIVES: In systematic reviews of interventions of studies where randomization was done by individual but data are paired (such as eyes, ears), it is necessary to account for the natural clustering present. The Cochrane Handbook suggests treating these as examples of cluster randomized trials. An incorrect analysis (without adjustment) would usually overestimate the precision of the estimate. We discuss a simple method of adjustment that deals with this problem. METHODS: From a cross-tabulation of the event being present on the "left" and "right" body part, we estimate the design effect which is a measure of the inflation on the variance due to clustering. This estimate is then used to obtain an adjusted effect size per trial by reducing the number of events and the sample size in each intervention group. RESULTS: In a systematic review on Auto-inflation for Glue Ear, data on improvement were obtained for pairs of ears. The design effect obtained from these data was 1.25. In a meta-analysis, the weights given to the trials changed after adjustment from 33% to 11% in one case. CONCLUSION: In a systematic review, when dealing with paired data, it is possible to give adequate weighting to each trial using a simple adjusting method.
Authors:
Rafael Perera; Paul Glasziou
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Publication Detail:
Type:  Journal Article     Date:  2007-05-04
Journal Detail:
Title:  Journal of clinical epidemiology     Volume:  60     ISSN:  0895-4356     ISO Abbreviation:  J Clin Epidemiol     Publication Date:  2007 Sep 
Date Detail:
Created Date:  2007-08-10     Completed Date:  2007-10-23     Revised Date:  2007-11-15    
Medline Journal Info:
Nlm Unique ID:  8801383     Medline TA:  J Clin Epidemiol     Country:  England    
Other Details:
Languages:  eng     Pagination:  975-8     Citation Subset:  IM    
Affiliation:
Department of Primary Health Care, University of Oxford, Rosemary Rue Building, Headington, OX3 7LF, Oxford, UK. rafael.perera@dphpc.ox.ac.uk
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MeSH Terms
Descriptor/Qualifier:
Cluster Analysis
Data Interpretation, Statistical*
Humans
Meta-Analysis as Topic*
Research Design
Sample Size

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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