Mega- or meta-analytic studies (e.g. genome-wide association (GWA) studies) are increasingly used in behavior genetics. Because phenotypes have not always been assessed similarly across cohorts (and sometimes not even within cohorts), measures need to be harmonized, that is, phenotypic scores need to be made comparable such that data from individuals who were assessed by different inventories can be compared meaningfully. Such harmonization then enables fixed effect meta-analytic analyses (Hedges and Vevea 1998). Meta-analytic studies are required when effect sizes are small such as for complex human traits. For example, GWA studies for psychiatric disorders have led to important discoveries, but for many disorders, individual variants typically explain less than 1 % of the heritability, although in unison they can explain quite a large proportion of phenotypic variation (Craddock et al. 2008; Lee et al. 2013; Ripke et al. 2013; Sullivan et al. 2012). Sample size determines the number of significant loci discovered (Sullivan et al. 2012), so that meta-analysis of results is the gold standard. Consortium GWA studies for traits such as height and body-mass index now report sample sizes
