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