Results from analyses of twin data that use models assuming a bivariate distribution of twin values will change when twins within pairs are reordered. We examined the effect of twin pair ordering on additive genetic variance estimates and hypothesis tests, from a bivariate normal model, both via simulation and through examination of real twin data. The simulations generated twin data for varying sample sizes and amounts of additive genetic and common environmental variance. The real data sets had sample sizes of 60 or less per zygosity. The results indicate that for moderate or large size studies, the effects of twin pair ordering are unlikely to greatly change the results of the data analysis; but for small studies the results can be sensitive to twin pair ordering. We therefore suggest that methods, not sensitive to within twin-pair differences be compared to the results obtained from twin-pair ordering. Methods not influenced by twin-pair ordering include least squares methods or covariance matrices approaches as described by Carey (2005, Behav Genet 35:667-670) or Guo and Wang (2002, Behav Genet 32:37-49).
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.