JSM 2005 - Toronto

Abstract #303720

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Activity Number: 320
Type: Contributed
Date/Time: Tuesday, August 9, 2005 : 2:00 PM to 3:50 PM
Sponsor: Biometrics Section
Abstract - #303720
Title: Modeling of Runaway Trajectories of Adolescents Using Zero-inflated Count Data
Author(s): Hayrettin Okut*+ and Terry E. Duncan and Susan W. Duncan
Companies: University of Yuzuncu Yil and Oregon Research Institute and Oregon Research Institute
Address: Yuzuncu Yil Universitesi, Van, 65080, Turkey
Keywords: Growth Mixture Modeling ; Zero-Inflated Poisson Regression ; Count Data ; runaway trajectories
Abstract:

Observed count data analyzed under Poisson regression models with a log-link function often have overdispersion, and the Poisson assumption of mean-variance equality is no longer valid for conditional on covariates. Poisson regression is widely used for excessive zeros and can be extended to negative binomial regression to allow for heterogeneity. Zero-inflated Poisson (ZIP) models provide a different way to model for count data with excess zeros under the Poisson assumption. The ZIP models assume the interested population consists of two types of individuals: one who gives a standard Poisson-distributed count with probability 1-p and another who always gives a zero count with probability p. Both the probabilities may depend on covariates. In the ZIP model, covariates could enter in two places: logit part and Poisson part. The covariates that affect the probability in logit and mean in the Poisson part could be the same. This study presents a ZIP growth mixture model to examine unobserved heterogeneity in runaway behaviors of a sample of 1,032 adolescents from a prospective longitudinal survey.

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