Andrew Booth writes:
>Does anyone have a simple explanation or "rule of thumb" for explaining to
>when a fixed effects or a random effects method should be used for a
There is a fair amount of controversy about this. I like to think of a
meta-analysis as a multi-center trial where each center uses a different
protocol. Since the multi-center trial requires random effects, so should a
The controversy occurs because many times there will be a sharp disagreement
between studies where some of them will cluster at one point and others will
cluster at a different point. This violates the assumption of normality for
the random effects model.
A new trend is to look for trends that might explain the underlying
heterogeneity (e.g., baseline risk) and incorporate these trends into a
model. This sometimes goes by the name of meta-regression.
Some people test for heterogeneity and then choose. I don't like this
approach--if there is little heterogeneity, the random and fixed models will
be close anyway, so why not always choose the random effects model?
I am not an expert in meta-analysis--just an informed consumer. So take my
comments with a grain of salt.
Steve Simon, [log in to unmask], Standard Disclaimer.
STATS: STeve's Attempt to Teach Statistics. http://www.cmh.edu/stats
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