Guest Editorial: Advances in Statistical Models and Methods

Abstract

A variety of recent methods and models are presented in this special issue devoted to advances in behavioral genetic methodology, ranging from tutorials to the introduction of new models and procedures that invite further exploration given their promising advantages. The articles included in this special issue can be organized under one or more of the following emergent themes: (a) alternatives to maximum likelihood (ML) estimation, (b) advantages of mixed effects software for fitting biometrical models, (c) testing for latent heterogeneity, and (d) violation of standard assumptions.