Influence of the slope in percentile estimation through binary regression for dose-finding experiments

Date

2024-12-04

Director

Publisher

Taylor & Francis
Acceso abierto / Sarbide irekia
Artículo / Artikulua
Versión publicada / Argitaratu den bertsioa

Project identifier

  • AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-116873GB-I00/ES/ recolecta
  • AEI/Plan Estatal de Investigación Científica y Técnica y de Innovación 2017-2020/PID2020-114031RB-I00/ES/ recolecta
Impacto
OpenAlexGoogle Scholar
No disponible en Scopus

Abstract

Dose-finding experiments aim to estimate the dose having a specified proportion of positive responses by collecting data in the vicinity of this unknown target dose. The importance of estimating the slope as well as a target dose has been recognized long ago in the literature. With large slopes at the target dose, a small error in the target dose estimate will be far from the target. Alternatively, with small slopes at the target, a large error conveys negligible changes on the associated response rate.  Thus a reasonably reliable estimate of the slope of the response function at the target dose should accompany every reported target dose estimate. Assuming a monotone increasing dose-response relationship, we work with a sizable catalogue of binary location-scale regression models parameterized by the target dose and the slope at the target. A compound design is proposed for the joint estimation of both features.

Description

Keywords

Compound optimal designs, Dose finding designs, Elfving's method

Department

Estadística, Informática y Matemáticas / Estatistika, Informatika eta Matematika

Faculty/School

Degree

Doctorate program

item.page.cita

Flournoy, N., Moler, J., Sada, M. (2024) Influence of the slope in percentile estimation through binary regression for dose-finding experiments. Statistics, 1-25. https://doi.org/10.1080/02331888.2024.2434903.

item.page.rights

© 2024 The Author(s). This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives License.

Licencia

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