A time‐varying effect model for examining group differences in trajectories of zero‐inflated count outcomes with applications in substance abuse research. (21st November 2016)

• Record Type: Journal Article
• Authors: Yang, Songshan; Cranford, James A.; Jester, Jennifer M.; Li, Runze; Zucker, Robert A.; Buu, Anne
• Is Part Of: Statistics in medicine. Volume 36:Number 5(2017)
• Page Start: 827
• Page End: 837
• Publication Date: 2016-11-21
• Subjects: time‐varying effect -- zero‐inflated Poisson model -- substance abuse -- longitudinal data -- B‐spline; Medical statistics -- Periodicals; Statistique médicale -- Périodiques; Statistiques médicales -- Périodiques; 610.727
• DOI: 10.1002/sim.7177
• Languages: English
• ISSNs: 0277-6715

Abstract

Abstract : This study proposes a time‐varying effect model for examining group differences in trajectories of zero‐inflated count outcomes. The motivating example demonstrates that this zero‐inflated Poisson model allows investigators to study group differences in different aspects of substance use (e.g., the probability of abstinence and the quantity of alcohol use) simultaneously. The simulation study shows that the accuracy of estimation of trajectory functions improves as the sample size increases; the accuracy under equal group sizes is only higher when the sample size is small (100). In terms of the performance of the hypothesis testing, the type I error rates are close to their corresponding significance levels under all settings. Furthermore, the power increases as the alternative hypothesis deviates more from the null hypothesis, and the rate of this increasing trend is higher when the sample size is larger. Moreover, the hypothesis test for the group difference in the zero component tends to be less powerful than the test for the group difference in the Poisson component. Copyright © 2016 John Wiley & Sons, Ltd.