DESIGN AND ANALYSIS OF INTRA-SUBJECT VARIABILITY IN CROSS-OVER EXPERIMENTS

✍ Scribed by VERNON M. CHINCHILLI; JAMES D. ESINHART

• Publisher: John Wiley and Sons
• Year: 1996
• Tongue: English
• Weight: 953 KB
• Volume: 15
• Category: Article
• ISSN: 0277-6715
• DOI: 10.1002/(sici)1097-0258(19960815)15:15<1619::aid-sim326>3.0.co;2-n

✦ Synopsis

Recently, interest has grown in the development of inferential techniques to compare treatment variabilities in the setting of a cross-over experiment. In particular, comparison of treatments with respect to intrasubject variability has greater interest than has inter-subject variability. We begin with a presentation of a general approach for statistical inference within a cross-over design. We discuss three different statistical models where model choice depends on the design and assumptions about carry-over effects. Each model incorporates t-variate random subject effects, where t is the number of treatments. We develop maximum likelihood (ML) and restricted maximum likelihood (REML) approaches to derive parameter estimators and we consider a special case in which closed-form expressions for the variance component estimators are available. Finally, we illustrate the methodologies with the analysis of data from three examples.