Related Experiment Video
Updated: Jul 4, 2026

A Pediatric Concussion Model in Mice: Closed Head Injury with Long-Term Disorders (CHILD)
Published on: February 7, 2025
Regression models for count data: illustrations using longitudinal predictors of childhood injury
Bryan T Karazsia1, Manfred H M van Dulmen
1Department of Psychology, Kent State University, Kent, OH 44242, USA. bkarazsi@kent.edu
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.
Related Concept Videos
Longitudinal Research
Survival Tree
Building a Survival Tree
Constructing a survival tree begins...
Regression Toward the Mean
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time until a...
Longitudinal Studies
Mechanistic Models: Compartment Models in Individual and Population Analysis