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CrossOver: an algorithm for the construction of efficient cross‐over designs
Author(s) -
John J. A.,
Russell K. G.,
Whitaker D.
Publication year - 2004
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.1860
Subject(s) - carry (investment) , crossover , computer science , flexibility (engineering) , algorithm , range (aeronautics) , construct (python library) , optimal design , mathematical optimization , mathematics , artificial intelligence , statistics , machine learning , engineering , finance , economics , programming language , aerospace engineering
A cross‐over experiment involves the application of sequences of treatments to several subjects over a number of time periods. It is thought that the observation made on each subject at the end of a time period may depend on the direct effect of the treatment applied in the current period, and the carry‐over effects of the treatments applied in one or more previous periods. Various models have been proposed to explain the nature of the carry‐over effects. An experimental design that is optimal under one model may not be optimal if a different model is the appropriate one. In this paper an algorithm is described to construct efficient cross‐over designs for a range of models that involve the direct effects of the treatments and various functions of their carry‐over effects. The effectiveness and flexibility of the algorithm are demonstrated by assessing its performance against numerous designs and models given in the literature. Copyright © 2004 John Wiley & Sons, Ltd.