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Optimal design of experiments for hypothesis testing on ordered treatments via intersection-union tests

Duarte, Belmiro P.M., Atkinson, Anthony C., P. Singh, Satya and S. Reis, Marco (2022) Optimal design of experiments for hypothesis testing on ordered treatments via intersection-union tests. Statistical Papers. ISSN 0932-5026

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Identification Number: 10.1007/s00362-022-01334-8

Abstract

We find experimental plans for hypothesis testing when a prior ordering of experimental groups or treatments is expected. Despite the practical interest of the topic, namely in dose finding, algorithms for systematically calculating good plans are still elusive. Here, we consider the Intersection-Union principle for constructing optimal experimental designs for testing hypotheses about ordered treatments. We propose an optimization-based formulation to handle the problem when the power of the test is to be maximized. This formulation yields a complex objective function which we handle with a surrogate-based optimizer. The algorithm proposed is demonstrated for several ordering relations. The relationship between designs maximizing power for the Intersection-Union Test (IUT) and optimality criteria used for linear regression models is analyzed; we demonstrate that IUT-based designs are well approximated by C–optimal designs and maximum entropy sampling designs while DA-optimal designs are equivalent to balanced designs. Theoretical and numerical results supporting these relations are presented.

Item Type: Article
Official URL: https://www.springer.com/journal/362
Additional Information: © 2022 The Authors, under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature
Divisions: Statistics
Subjects: H Social Sciences > HA Statistics
Date Deposited: 24 May 2022 14:03
Last Modified: 29 Jun 2022 15:39
URI: http://eprints.lse.ac.uk/id/eprint/115187

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