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Making Sense of Data Analytic Techniques used in a Cochrane Systematic Review

Published online by Cambridge University Press:  15 January 2018

Paul Gertler*
Affiliation:
The John Walsh Centre for Rehabilitation Research, Northern Clinical School, The University of Sydney, Australia
Ian D. Cameron
Affiliation:
The John Walsh Centre for Rehabilitation Research, Northern Clinical School, The University of Sydney, Australia
*
Address for correspondence: Paul Gertler, John Walsh Centre for Rehabilitation Research, The University of Sydney, Kolling Institute of Medical Research, Royal North Shore Hospital, St Leonards NSW, 2065Australia. E-mail: pger8510@uni.sydney.edu.au
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Abstract

Systematic reviews have developed over the past 40 years as a method for integrating findings from the available studies relating to clinical problems and interventions into one publication. Systematic reviews employ a variety of data analytic techniques including meta-analysis, which combines treatment effects across disparate studies in order to produce a truer estimate of treatment effect. The Cochrane Collaboration was established in order to facilitate access to high-quality evidence and specifies stringent guidelines for the production of systematic reviews. A Cochrane Systematic Review (CSR) includes consideration of the risk-of-bias of the selected studies in reaching conclusions. A recent CSR is used as an example to demonstrate the process of conducting a CSR, the data analytic methods employed and the assumptions made when employing these methods. There is a discussion of issues the reader will need to be aware of when considering the findings of a CSR and how this might differ from other systematic reviews including some consideration of how CSRs apply to the brain impairment literature.

Type
Articles
Copyright
Copyright © Australasian Society for the Study of Brain Impairment 2018 

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