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On Applying Optimal Design of Experiments when Functional Observations Occur Read chapter Read first chapter

2016 | OriginalPaper | Chapter

Study Designs for the Estimation of the Hill Parameter in Sigmoidal Response Models

Author : Tobias Mielke

Published in: mODa 11 - Advances in Model-Oriented Design and Analysis

Publisher: Springer International Publishing

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Abstract

Sigmoidal models are frequently considered for the description of the dose-response relationship in dose-finding studies. Designs for these models depend on unknown parameters, which enter the model in a nonlinear way. A particular problem in frequentistic analysis using the sigmoid EMax model is the estimation of the Hill parameter, which may be problematic to estimate. The estimation problem for the Hill parameter and a model-based design approach to limit this problem will be examined in this paper.

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previous chapter Conditional Inference in Two-Stage Adaptive Experiments via the Bootstrap
next chapter Controlled Versus “Random” Experiments: A Principle
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Metadata
Title
Study Designs for the Estimation of the Hill Parameter in Sigmoidal Response Models
Author
Tobias Mielke
Copyright Year
2016
Book
mODa 11 - Advances in Model-Oriented Design and Analysis

Print ISBN: 978-3-319-31264-4

Electronic ISBN: 978-3-319-31266-8

Copyright Year: 2016

DOI
https://doi.org/10.1007/978-3-319-31266-8_21

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