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An application of Polya theory to cross-over designs with dropout

An application of Polya theory to cross-over designs with dropout
An application of Polya theory to cross-over designs with dropout
Cross-over experiments in, for example, clinical and medical research often have subjects (patients) who fail to complete the sequence of treatments allocated to them in the planned design. Methodology has been developed for evaluating the robustness of a cross over design to such dropouts. Implementing the methodology requires the assessment of a large number of designs and is computationally demanding, even for studies involving small numbers of subjects. This paper establishes an analogy between the design problem and enumeration problems encountered in combinatorial theory. It shows how the computations can be substantially reduced by applying results associated with Polya theory making feasible an evaluation of the robustness of a design.
0315-3681
129-142
Low, J.L.
992453ba-0119-4263-b2b4-89bacd9830a4
Lewis, S.M.
a69a3245-8c19-41c6-bf46-0b3b02d83cb8
Prescott, P.
cf0adfdd-989b-4f15-9e60-ef85eed817b2
Low, J.L.
992453ba-0119-4263-b2b4-89bacd9830a4
Lewis, S.M.
a69a3245-8c19-41c6-bf46-0b3b02d83cb8
Prescott, P.
cf0adfdd-989b-4f15-9e60-ef85eed817b2

Low, J.L., Lewis, S.M. and Prescott, P. (2003) An application of Polya theory to cross-over designs with dropout. Utilitas Mathematica, 63, 129-142.

Record type: Article

Abstract

Cross-over experiments in, for example, clinical and medical research often have subjects (patients) who fail to complete the sequence of treatments allocated to them in the planned design. Methodology has been developed for evaluating the robustness of a cross over design to such dropouts. Implementing the methodology requires the assessment of a large number of designs and is computationally demanding, even for studies involving small numbers of subjects. This paper establishes an analogy between the design problem and enumeration problems encountered in combinatorial theory. It shows how the computations can be substantially reduced by applying results associated with Polya theory making feasible an evaluation of the robustness of a design.

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More information

Published date: May 2003
Organisations: Statistics

Identifiers

Local EPrints ID: 30074
URI: http://eprints.soton.ac.uk/id/eprint/30074
ISSN: 0315-3681
PURE UUID: b4f26225-c15f-4628-aaaf-1bd119896bd8

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Date deposited: 08 Jan 2007
Last modified: 27 Apr 2022 08:45

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Contributors

Author: J.L. Low
Author: S.M. Lewis
Author: P. Prescott

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