Regression models for count data: illustrations using longitudinal predictors of childhood injury

J Pediatr Psychol. Nov-Dec 2008;33(10):1076-84. doi: 10.1093/jpepsy/jsn055. Epub 2008 Jun 3.

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.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Attention
  • Attention Deficit Disorder with Hyperactivity / epidemiology
  • Attention Deficit Disorder with Hyperactivity / psychology
  • Child
  • Child, Preschool
  • Cross-Sectional Studies
  • Female
  • Humans
  • Impulsive Behavior / epidemiology
  • Impulsive Behavior / psychology
  • Longitudinal Studies
  • Male
  • National Institute of Child Health and Human Development (U.S.)
  • Parent-Child Relations
  • Poisson Distribution
  • Prospective Studies
  • Regression Analysis
  • Risk
  • Safety
  • Social Environment
  • Temperament
  • United States
  • Wounds and Injuries / epidemiology*
  • Wounds and Injuries / psychology