Some analysis strategies for three-period changeover designs with two treatments.
Alternative analysis strategies for the three-period crossover design with two treatments are discussed in this paper. One analysis strategy involves a parametric model that incorporates the effects of interest. To implement this method, one usually assumes that the covariance structure for the data has the sphericity, or circularity, property. Alternative approaches that do not require this assumption are described. They are based on the parametric and non-parametric analysis of appropriate within-subject linear functions of the data. The advantage of these methods is that one only needs the assumption that the resulting linear functions for the respective subjects are independent and have a common distribution. The parametric approach also requires normality of the resulting within-subject linear functions for small sample situations. An extension of the non-parametric method is considered for cases in which the treatment sequences are randomly assigned within strata. The various methods are illustrated for a three-period crossover design involving two strata with randomly assigned treatment sequences of the form A:B:A and B:A:B.
Hafner
K B
KB
Department of Biostatistics, University of North Carolina, Chapel Hill 27514.
Koch
G G
GG
Canada
A T
AT
D000818:Animals; D005260:Female; D051379:Mice; D010126:Ozone / Q000494:pharmacology; D010424:Pentobarbital / Q000493:pharmacokinetics; D010600:Pharmacology / Q000379:methods; D012107:Research Design; D012890:Sleep / Q000187:drug effects; D013223:Statistics as Topic
D010126:Ozone; D010424:Pentobarbital