The investigation of heterogeneity is a crucial part of any meta-analy
sis. While it has been stated that the test for heterogeneity has low
power, this has not been well quantified. Moreover the assumptions of
normality implicit in the standard methods of meta-analysis are often
not scrutinized in practice. Here we simulate how the power of the tes
t for heterogeneity depends on the number of studies included, the tot
al information (that is total weight or inverse variance) available an
d the distribution of weights among the different studies. We show tha
t the power increases with the total information available rather than
simply the number of studies, and that it is substantially lowered if
, as is quite common in practice, one study comprises a large proporti
on of the total information. We also describe normal plots that are us
eful in assessing whether the data conform to a fixed effect or random
effects model, together with appropriate tests, and give an applicati
on to the analysis of a multi-centre trial of blood pressure reduction
. We conclude that the test of heterogeneity should not be the sole de
terminant of model choice in meta-analysis, and inspection of relevant
normal plots, as well as clinical insight, may be more relevant to bo
th the investigation and modelling of heterogeneity. (C) 1998 John Wil
ey & Sons, Ltd.