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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