The conventional choice of distribution is a normal distribution. The centre of this distribution describes the average of the effects, while its width describes the degree of heterogeneity. The model represents our lack of knowledge about why real, or apparent, intervention effects differ by considering the differences as if they were random. A random-effects meta-analysis model involves an assumption that the effects being estimated in the different studies are not identical, but follow some distribution. When there is heterogeneity that cannot readily be explained, one analytical approach is to incorporate it into a random-effects model. that there is no statistical heterogeneity. This assumption implies that the observed differences among study results are due solely to the play of chance, i.e. In order to calculate a confidence interval for a fixed-effect meta-analysis the assumption is made that the true effect of intervention (in both magnitude and direction) is the same value in every study (that is, fixed across studies). 9.5.4 Incorporating heterogeneity into random-effects modelsĪ fixed-effect meta-analysis provides a result that may be viewed as a ‘typical intervention effect’ from the studies included in the analysis. For the current version, please go to /handbook/current or search for this chapter here. This is an archived version of the Handbook.