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A note on ANOVA assumptions and robust analysis for a cross‐over study
Author(s) -
Chen Xun,
Zhao PengLiang,
Zhang Ji
Publication year - 2002
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.1103
Subject(s) - analysis of variance , mixed design analysis of variance , statistics , variance (accounting) , computer science , repeated measures design , econometrics , set (abstract data type) , mathematics , accounting , business , programming language
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. Copyright © 2002 John Wiley & Sons, Ltd.