Clarifying identification and estimation of treatment effects in the Sequential Parallel Comparison Design

Fuente: arXiv
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Main Authors: Stockton, Benjamin, Santacatterina, Michele, Mandal, Soutrik, Cleland, Charles M., Hade, Erinn M., Illenberger, Nicholas, Meropol, Sharon, Troxel, Andrea B., Petkova, Eva, Yu, Chang, Tarpey, Thaddeus
Format: Preprint
Published: 2025
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_version_ 1866911371130568704
author Stockton, Benjamin
Santacatterina, Michele
Mandal, Soutrik
Cleland, Charles M.
Hade, Erinn M.
Illenberger, Nicholas
Meropol, Sharon
Troxel, Andrea B.
Petkova, Eva
Yu, Chang
Tarpey, Thaddeus
author_facet Stockton, Benjamin
Santacatterina, Michele
Mandal, Soutrik
Cleland, Charles M.
Hade, Erinn M.
Illenberger, Nicholas
Meropol, Sharon
Troxel, Andrea B.
Petkova, Eva
Yu, Chang
Tarpey, Thaddeus
contents 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.
format Preprint
id arxiv_https___arxiv_org_abs_2511_19677
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle Clarifying identification and estimation of treatment effects in the Sequential Parallel Comparison Design
Stockton, Benjamin
Santacatterina, Michele
Mandal, Soutrik
Cleland, Charles M.
Hade, Erinn M.
Illenberger, Nicholas
Meropol, Sharon
Troxel, Andrea B.
Petkova, Eva
Yu, Chang
Tarpey, Thaddeus
Methodology
Applications
62P10
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.
title Clarifying identification and estimation of treatment effects in the Sequential Parallel Comparison Design
topic Methodology
Applications
62P10
url https://arxiv.org/abs/2511.19677