A note on ANOVA assumptions and robust analysis for a cross-over study.
Analysis of variance (ANOVA) methods are usually applied to analyse continuous data from cross-over studies. The analysis, however, may not have appropriate type I error when certain assumptions are violated. In this paper, we first clarify a conventionally minimum set of assumptions that validate the F-tests of ANOVA models for cross-over studies. We then provide a practical verification/remedy procedure based upon the theoretical developments. By applying the verification/remedy procedure, more robust analysis results can be expected from the ANOVA models.
Chen
Xun
X
Clinical Biostatistics, Merck Research Laboratories, RY34-A316, Rahway, NJ 07065, USA. Xun_Chen@Merck.Com
Zhao
Peng-Liang
PL
Zhang
Ji
J
D000704:Analysis of Variance; D000959:Antihypertensive Agents / Q000494:pharmacology; D001794:Blood Pressure / Q000187:drug effects; D018592:Cross-Over Studies; D006801:Humans; D015233:Models, Statistical
D000959:Antihypertensive Agents