Local Optima in Mixture Modeling.

It is common knowledge that mixture models are prone to arrive at locally optimal solutions. Typically, researchers are directed to utilize several random initializations to ensure that the resulting solution is adequate. However, it is unknown what factors contribute to a large number of local optima and whether these coincide with the factors that reduce the accuracy of a mixture model.

Sex differences in the latent class structure of alcohol use disorder: Does (dis)aggregation of indicators matter?

Many researchers have argued for a differential presentation of alcohol use disorder (AUD) between men and women. Latent class analysis is the most commonly used analytic technique for modeling AUD subcategories, and latent class analyses have supported a variety of class structures of AUD. This article examines whether these differential results are, in part, an artifact of whether researchers have (a) analyzed men and women in the same analysis and (b) aggregated item-level symptoms into AUD diagnostic criteria prior to analysis.