Missing Data in Alcohol Clinical Trials with Binary Outcomes.

ABSTRACT:

Background

Missing data are common in alcohol clinical trials for both continuous and binary end points. Approaches to handle missing data have been explored for continuous outcomes, yet no studies have compared missing data approaches for binary outcomes (e.g., abstinence, no heavy drinking days). This study compares approaches to modeling binary outcomes with missing data in the COMBINE study.

Methods

We included participants in the COMBINE study who had complete drinking data during treatment and who were assigned to active medication or placebo conditions (N = 1,146). Using simulation methods, missing data were introduced under common scenarios with varying sample sizes and amounts of missing data. Logistic regression was used to estimate the effect of naltrexone (vs. pl

SUBMITTER: Hallgren KA 

PROVIDER: S-EPMC5522809 | biostudies-literature | 2016 Jul

REPOSITORIES: biostudies-literature