An evaluation of different approaches for behavior genetic analyses with psychiatric symptom scores

We used a simulation study to evaluate six approaches for behavior genetic analyses of psychiatric symptom scores. For the selection of the correct mo del, the best results were obtained with approaches using transformed score s in combination with a procedure involving p-values. With normalizing tran sformations, the chi(2) test statistic gave a reasonable impression of the overall fit of the model but was less accurate when used as a difference te st. The asymptotic distribution free estimation methods yielded chi(2)s tha t were much too large. All data analysis techniques yielded substantially b iased parameter estimates. The most biased results were obtained with norma lizing transformations. The least biased results were obtained with tobit c orrelations, but because of its large standard errors the most precise esti mates were obtained with polychoric correlations and optimal scale scores. An empirical study showed that a recognition of the role of methodological factors was helpful to understand parr of the differences between assessmen t instruments, raters, and data analysis techniques that were found in the real data.