Clarifying identification and estimation of treatment effects in the Sequential Parallel Comparison Design
Abstract
Sequential parallel comparison design (SPCD) clinical trials aim to adjust active treatment effect estimates for placebo response to minimize the impact of placebo responders on the estimates. This is potentially accomplished using a two stage design by measuring treatment effects among all participants during the first stage, then classifying some placebo arm participants as placebo non-responders who will be re-randomized in the second stage. In this paper, we use causal inference tools to clarify under what assumptions treatment effects can be identified in SPCD trials and what effects the conventional estimators target at each stage of the SPCD trial. We further illustrate the highly influential impact of placebo response misclassification on the second stage estimate. We conclude that the conventional SPCD estimators do not target meaningful treatment effects.
Cite
@article{arxiv.2511.19677,
title = {Clarifying identification and estimation of treatment effects in the Sequential Parallel Comparison Design},
author = {Benjamin Stockton and Michele Santacatterina and Soutrik Mandal and Charles M. Cleland and Erinn M. Hade and Nicholas Illenberger and Sharon Meropol and Andrea B. Troxel and Eva Petkova and Chang Yu and Thaddeus Tarpey},
journal= {arXiv preprint arXiv:2511.19677},
year = {2026}
}
Comments
21 pages Update: Added discussion of Song et al. (2025) in Section 1 & 6. Added an illustrative example in Section 5