Behavioral Carry-Over Effect and Power Consideration in Crossover Trials

TL;DR

This paper examines the effects of behavioral carry-over in crossover trials, highlighting how it can bias treatment effect estimates and affect statistical power, and proposes methods to address these issues within a potential outcomes framework.

Contribution

It provides a theoretical analysis of carry-over effects in crossover trials, deriving conditions for when crossover designs are preferable and developing covariate adjustment methods.

Findings

Carry-over effects can bias treatment estimates under certain conditions.

Crossover design can be more powerful than parallel-group design if specific criteria are met.

Covariate adjustment improves the accuracy and power of crossover trials.

Abstract

A crossover trial is an efficient trial design when there is no carry-over effect. To reduce the impact of the biological carry-over effect, a washout period is often designed. However, the carry-over effect remains an outstanding concern when a washout period is unethical or cannot sufficiently diminish the impact of the carry-over effect. The latter can occur in comparative effectiveness research where the carry-over effect is often non-biological but behavioral. In this paper, we investigate the crossover design under a potential outcomes framework with and without the carry-over effect. We find that when the carry-over effect exists and satisfies a sign condition, the basic estimator underestimates the treatment effect, which does not inflate the type I error of one-sided tests but negatively impacts the power. This leads to a power trade-off between the crossover design and the parallel-group design, and we derive the condition under which the crossover design does not lead to type I error inflation and is still more powerful than the parallel-group design. We also develop covariate adjustment methods for crossover trials. We evaluate the performance of cross-over design and covariate adjustment using data from the MTN-034/REACH study.