JSM 2015 Preliminary Program

Online Program Home
My Program

Abstract Details

Activity Number: 243
Type: Contributed
Date/Time: Monday, August 10, 2015 : 2:00 PM to 3:50 PM
Sponsor: Mental Health Statistics Section
Abstract #316579 View Presentation
Title: Autoregressive Latent Class Models for Longitudinal Count Data
Author(s): Nicholas C. Henderson* and Paul J. Rathouz
Companies: University of Wisconsin - Madison and University of Wisconsin - Madison
Keywords: Discrete AR(1) processes ; Class discrimination ; Finite mixture model ; Longitudinal data ; Negative binomial model
Abstract:

In a variety of applications involving longitudinal or repeated-measurements data, it is desired to uncover natural groupings or clusters which exist among study subjects. Motivated by the need to recover longitudinal trajectories of conduct problems in the field of developmental psychopathology, we propose a method to address this goal when the data in question are counts. We assume that the subject-specific observations are generated from a first-order autoregressive process which is appropriate for counts. A key advantage of our approach is that the marginal distribution of the response can be expressed in closed form, circumventing computational issues associated with random effects models. Additionally, we introduce a novel method to express the degree to which both the underlying data and the fitted model are able to correctly assign subjects to their latent classes. We explore the effectiveness of our procedures through simulations based on a four-class model, placing a special emphasis on posterior classification. Finally, we analyze data and recover trajectories of conduct problems in an important nationally representative sample.


Authors who are presenting talks have a * after their name.

Back to the full JSM 2015 program





For program information, contact the JSM Registration Department or phone (888) 231-3473.

For Professional Development information, contact the Education Department.

The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.

2015 JSM Online Program Home