CrossOver: an algorithm for the construction of efficient cross-over designs.
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.
John
J A
JA
Department of Statistics, University of Waikato, Hamilton, New Zealand. nye@stats.waikato.ac.nz
Russell
K G
KG
Whitaker
D
D
D000465:Algorithms; D002986:Clinical Trials as Topic / Q000379:methods*; D018592:Cross-Over Studies; D006801:Humans; D015233:Models, Statistical; D012107:Research Design