Related Experiment Video
Updated: Dec 6, 2025

Inverse Probability of Treatment Weighting Propensity Score using the Military Health System Data Repository and National Death Index
Published on: January 8, 2020
Statistical properties of Continuous Composite Outcomes: Implications for clinical trial design
Jesse D Troy1,2, Ryan A Simmons2
1The Marcus Center for Cellular Cures, Duke University School of Medicine, USA.
Abstract:
Statistical efficiency can be gained in clinical trials by using composites of time-to-event outcomes when the individual component outcomes have low event rates. However, the utility of continuous composite outcome measures is not as clear. Efficiency can be either gained or lost by using a continuous composite outcome measure depending on several factors, including the strength of correlation between the component outcomes and the size of the treatment effect on each component. In this article we review these concepts from the standpoint of planning a new trial. Statistical properties of composites formed from normally distributed continuous outcomes are discussed. An example dataset is used to demonstrate concepts and complete mathematical details are provided. Finally, a conceptual model for clinical trial design with continuous composites is proposed that could be used as a guide to evaluate the utility of a continuous composite outcome in a future trial based on existing knowledge in the therapeutic area.
Related Concept Videos
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast,...
Assumptions of Survival Analysis
Biostatistics: Overview
Discrete variables are...
Study Design in Statistics
Does aspirin reduce the risk of heart attacks? Is one brand of fertilizer more effective at growing roses than another? Is fatigue as dangerous to a driver as the influence of alcohol? Questions like these are answered using randomized experiments with proper...
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups

