Optimal monotone conditional error functions

Fuente: arXiv
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Autores principales: Brannath, Werner, Dreher, Morten, Scharpenberg, Martin
Formato: Preprint
Publicado: 2024
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author Brannath, Werner
Dreher, Morten
Scharpenberg, Martin
author_facet Brannath, Werner
Dreher, Morten
Scharpenberg, Martin
contents This note presents a method that provides optimal monotone conditional error functions for a large class of adaptive two stage designs. The presented method builds on a previously developed general theory for optimal adaptive two stage designs where sample sizes are reassessed for a specific conditional power and the goal is to minimize the expected sample size. The previous theory can easily lead to a non-monotonous conditional error function which is highly undesirable for logical reasons and can harm type I error rate control for composite null hypotheses. The here presented method extends the existing theory by introducing intermediate monotonising steps that can easily be implemented.
format Preprint
id arxiv_https___arxiv_org_abs_2402_00814
institution arXiv
publishDate 2024
record_format arxiv
spellingShingle Optimal monotone conditional error functions
Brannath, Werner
Dreher, Morten
Scharpenberg, Martin
Methodology
This note presents a method that provides optimal monotone conditional error functions for a large class of adaptive two stage designs. The presented method builds on a previously developed general theory for optimal adaptive two stage designs where sample sizes are reassessed for a specific conditional power and the goal is to minimize the expected sample size. The previous theory can easily lead to a non-monotonous conditional error function which is highly undesirable for logical reasons and can harm type I error rate control for composite null hypotheses. The here presented method extends the existing theory by introducing intermediate monotonising steps that can easily be implemented.
title Optimal monotone conditional error functions
topic Methodology
url https://arxiv.org/abs/2402.00814