At 15.40 20/08/01 +0000, Andrew Booth wrote:
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Does anyone have a simple explanation or "rule of thumb" for explaining to people when a fixed effects or a random effects method should be used for a systematic review.

From
Meta-analysis: principles and procedures. BMJ 1997;315:1533-7
http://www.bmj.com/archive/7121/7121ed.htm

Statistical methods for calculating overall effect
A simple arithmetic average of the results from all the trials would give misleading results. The results from small studies are more subject to the play of chance and should therefore be given less weight. Methods used for meta-analysis use a weighted average of the results, in which the larger trials have more influence than the smaller ones. The statistical techniques to do this can be broadly classified into two models, the difference consisting in the way the variability of the results between the studies is treated. The "fixed effects" model considers, often unreasonably, that this variability is exclusively due to random variation. Therefore, if all the studies were infinitely large they would give identical results. The "random effects" model assumes a different underlying effect for each study and takes this into consideration as an additional source of variation, which leads to somewhat wider confidence intervals than the fixed effects model. Effects are assumed to be randomly distributed, and the central point of this distribution is the focus of the combined effect estimate. Although neither of two models can be said to be "correct," a substantial difference in the combined effect calculated by the fixed and random effects models will be seen only if studies are markedly heterogeneous.

You can read also:
Lau J, Ioannidis JPA, Schmid CH. Quantitative synthesis in systematic reviews. Ann Intern Med 1997;127:820-26
http://www.acponline.org/journals/annals/01nov97/quantsyn.htm


Bests




Nino Cartabellotta, MD
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GSM Phone +39-339-6443819

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