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Journal of Pediatric Psychology Advance Access published online on June 3, 2008
Journal of Pediatric Psychology, doi:10.1093/jpepsy/jsn055
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© The Author 2008. Published by Oxford University Press on behalf of the Society of Pediatric Psychology. All rights reserved. For permissions, please e-mail: journals.permissions@oxfordjournals.org

Regression Models for Count Data: Illustrations using Longitudinal Predictors of Childhood Injury*

Bryan T. Karazsia, MA and Manfred H. M. van Dulmen, PHD

Kent State University

All correspondence concerning this article should be addressed to Bryan T. Karazsia, Department of Psychology, Kent State University, Kent, OH 44242, USA. E-mail: bkarazsi{at}kent.edu


  Abstract

Objective To offer a practical demonstration of regression models recommended for count outcomes using longitudinal predictors of children's medically attended injuries. Method Participants included 708 children from the NICHD child care study. Measures of temperament, attention, parent–child relationship, and safety of physical environment were used to predict medically attended injuries. Results Statistical comparisons among five estimation methods revealed that a zero-inflated Poisson (ZIP) model provided the best fit with observed data. ZIP models simultaneously model dichotomous and continuous outcomes of count variables, and different constellations of predictors emerged for each aspect of the estimated model. Conclusions This study offers a practical demonstration of techniques designed to handle dependent count variables. The conceptual and statistical advantages of these methods are emphasized, and Stata script is provided to facilitate adoption of these techniques.

Key words: count data; injury; regression.

*Portions of this article were presented at the 2008 National Conference in Child Health Psychology, Miami, FL.

Received December 13, 2007; revision received May 5, 2008; accepted May 13, 2008


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