Optimum design and sequential treatment allocation in an experiment in deep brain stimulation with sets of treatment combinations

Atkinson, Anthony and Pedrosa, David (2017) Optimum design and sequential treatment allocation in an experiment in deep brain stimulation with sets of treatment combinations. Statistics in Medicine, 36 (30). pp. 4804-4815. ISSN 0277-6715

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Abstract

In an experiment including patients who underwent surgery for deep brain stimulation electrode placement, each patient responds to a set of 9 treatment combinations. There are 16 such sets, and the design problem is to choose which sets should be administered and in what proportions. Extensions to the methods of nonsequential optimum experimental design lead to identification of an unequally weighted optimum design involving 4 sets of treatment combinations. In the actual experiment, patients arrive sequentially and present with sets of prognostic factors. The idea of loss due to Burman is extended and used to assess designs with varying randomization structures. It is found that a simple sequential design using only 2 sets of treatments has surprisingly good properties for trials with the proposed number of patients.

Item Type:	Article
Official URL:	http://onlinelibrary.wiley.com/journal/10.1002/(IS...
Additional Information:	© 2017 John Wiley & Sons, Ltd.
Divisions:	Statistics
Subjects:	Q Science > QA Mathematics R Medicine > RA Public aspects of medicine > RA0421 Public health. Hygiene. Preventive Medicine
Date Deposited:	12 Mar 2018 15:02
Last Modified:	27 Feb 2024 00:10
URI:	http://eprints.lse.ac.uk/id/eprint/87157

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