01. Zero Inflated Outcomes in SMART Designs

A Sequential, Multiple Assignment, Randomized Trial (SMART) is a type of clinical trial design that allows for the development, estimation and comparison of dynamic treatment regimens or tailored sequences of treatments. Typical methods for analyzing outcomes from a SMART utilize weighted and replicated regression. When dealing with count outcomes, especially in settings of substance use, zero-inflation can be a common issue.

One common approach to handling zero-inflated outcomes for standard, longitudinal data is a two-part hurdle model (HM) which addresses sampling or random zero outcomes. Sampling zeros occur when all individuals have zeroes in their outcome but are still at risk of an event. HMs have yet to be applied to SMART data.

We develop a two-part HM to address zero-inflated outcomes in the SMART setting with longitudinal, count outcomes. In this approach, one part of the model is a logistic regression with a binary zero / nonzero indicator outcome, and the second part is a truncated Poisson model for the nonzero count outcomes. We were motivated by and apply our method to a recently completed SMART, the SafERteens M-Coach trial which investigated the effects of brief interventions and text messaging on young adults considering the outcome of alcohol consumption.

Sequential Multiple Assignment Randomized Trial (SMART)

Zero-Inflated Outcomes

Clinical Trial Methods

Poisson Regression

Longitudinal Data 

Mid-Level

Knowledge

Women in Statistics and Data Science 2025