Assessing exposure‐time treatment effect heterogeneity in stepped‐wedge cluster randomized trials

Lara Maleyeff, Fan Li, Sebastien Haneuse and Rui Wang

Biometrics, 2023, vol. 79, issue 3, 2551-2564

Abstract: A stepped‐wedge cluster randomized trial (CRT) is a unidirectional crossover study in which timings of treatment initiation for clusters are randomized. Because the timing of treatment initiation is different for each cluster, an emerging question is whether the treatment effect depends on the exposure time, namely, the time duration since the initiation of treatment. Existing approaches for assessing exposure‐time treatment effect heterogeneity either assume a parametric functional form of exposure time or model the exposure time as a categorical variable, in which case the number of parameters increases with the number of exposure‐time periods, leading to a potential loss in efficiency. In this article, we propose a new model formulation for assessing treatment effect heterogeneity over exposure time. Rather than a categorical term for each level of exposure time, the proposed model includes a random effect to represent varying treatment effects by exposure time. This allows for pooling information across exposure‐time periods and may result in more precise average and exposure‐time‐specific treatment effect estimates. In addition, we develop an accompanying permutation test for the variance component of the heterogeneous treatment effect parameters. We conduct simulation studies to compare the proposed model and permutation test to alternative methods to elucidate their finite‐sample operating characteristics, and to generate practical guidance on model choices for assessing exposure‐time treatment effect heterogeneity in stepped‐wedge CRTs.

Date: 2023
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