ENAR 2015SPRING MEETING With IMS & Sections of ASA MARCH 15 –18 Hyatt Regency Miami Miami, FL ABSTRACTS ENAR 2015 dimensions are found if the excess zeroes are Abstracts & Poster accounted for correctly. A mixture model, i.e. hybrid latent class latent factor model, is used to assess Presentations the dimensionality of the underlying subgroup cor- responding to those who come from the part of the population with some measurable trait. Implications 1. POSTERS: of the findings are discussed, in particular regard- Latent Variable and ing the potential for different findings in community Mixture Models versus patient populations. email:
[email protected] 1a. ASSESSMENT OF DIMENSIONALITY CAN BE DISTORTED BY TOO MANY ZEROES: 1b. LOCAL INFLUENCE DIAGNOSTICS AN EXAMPLE FROM PSYCHIATRY AND FOR HIERARCHICAL COUNT DATA A SOLUTION USING MIXTURE MODELS MODELS WITH OVERDISPERSION AND EXCESS ZEROS Melanie M. Wall*, Columbia University Trias Wahyuni Rakhmawati*, Universiteit Hasselt Irini Moustaki, London School of Economics Geert Molenberghs, Universiteit Hasselt and Common methods for determining the number of Katholieke Universiteit Leuven latent dimensions underlying an item set include eigenvalue analysis and examination of fit statistics Geert Verbeke, Katholieke Universiteit Leuven for factor analysis models with varying number of and Universiteit Hasselt factors. Given a set of dichotomous items, we will Christel Faes, Universiteit Hasselt and Katholieke demonstrate that these empirical assessments of Universiteit Leuven dimensionality are likely to underestimate the num- ber of dimensions when there is a preponderance We consider models for hierarchically observed of individuals in the sample with all zeros as their and possibly overdispersed count data, that in responses, i.e.