Methods of fixed effect meta-analysis are based on the assumption that a single common (or ‘fixed’) effect underlies every study in the meta-analysis, i.e. if every study were infinitely large, the results of every study would be identical because there is no between-study heterogeneity. Fixed effects analysis provides for testing of the null hypothesis of no association in any of the study populations being analyzed. This is useful if we simply aim to optimize power for detecting association. However, if heterogeneity exists, then this association may not be possible to extend equally well to diverse populations.
