INCORPORATING VARIABILITY IN ESTIMATES OF HETEROGENEITY IN THE RANDOMEFFECTS MODEL IN METAANALYSIS

When combining results from separate investigations in a meta-analysis , random effects methods enable the modelling of differences between s tudies by incorporating a heterogeneity parameter tau(2) that accounts explicitly for across-study variation. We develop a simple form for t he variance of Cochran's homogeneity statistic Q, leading to interval estimation of tau(2) utilizing an approximating distribution for Q; th is enables us to extend the point estimation of DerSimonian and Laird. We also develop asymptotic likelihood methods and compared them with this method. We then use these approximating distributions to give a n ew method of calculating the weight given to the individual studies' r esults when estimating the overall mean which takes into account varia tion in these point estimates of tau(2). Two examples illustrate the m ethods presented, where we show that the new weighting scheme is betwe en the standard fixed and random effects models in down-weighting the results of large studies and up-weighting those of small studies. (C) 1997 by John Wiley & Sons, Ltd.