Analysis of cross-over designs with serial correlation within periods using semi-parametric mixed models.
The use of semi-parametric mixed models has proven useful in a wide variety of settings. Here, we focus on the application of the methodology in the particular case of a cross-over design with relatively long sequences of repeated measurements within each treatment period and for each subject. Other than an overall measure of the difference between each one of the experimental groups and the control group, specific time point comparisons may also be of interest. To that effect, we propose the use of flexible semi-parametric mixed models, enabling the construction of simulation-based simultaneous confidence bands. The bands take into account both between- and within-subject variabilities, while simultaneously correcting for multiple time point comparisons. Owing to the relatively long sequences of measurements per subject, the presence of serially correlated errors is anticipated and investigated. We illustrate how several formulations of semi-parametric mixed models can be fitted and the construction of simulation-based simultaneous confidence bands using SAS PROC MIXED.
Maringwa
John T
JT
Center for Statistics, Hasselt University, BE3590 Diepenbeek, Belgium. john.maringwa@uhasselt.be
Geys
Helena
H
Shkedy
Ziv
Z
Faes
Christel
C
Molenberghs
Geert
G
Aerts
Marc
M
Van Ammel
Karel
K
Teisman
Ard
A
Bijnens
Luc
L
D000818:Animals; D019540:Area Under Curve; D001699:Biometry; D018592:Cross-Over Studies; D003627:Data Interpretation, Statistical; D004285:Dogs; D006321:Heart / Q000187:drug effects; D016013:Likelihood Functions; D015233:Models, Statistical; D018709:Statistics, Nonparametric