Generalizability in nongaussian longitudinal clinical trial data based on generalized linear mixed models.
This work investigates how generalizability, an extension of reliability, can be defined and estimated based on longitudinal data sequences resulting from, for example, clinical studies. Useful and intuitive approximate expressions are derived based on generalized linear mixed models. Data from four double-blind, randomized clinical trials into schizophrenia motivate the research and are used to estimate generalizability for a binary response parameter.
Vangeneugden
Tony
T
Tibotec, Johnson & Johnson, Mechelen, Belgium. tvangene@tibbe.jnj.com
Molenberghs
Geert
G
Laenen
Annouschka
A
Alonso
Ariel
A
Geys
Helena
H
D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D016014:Linear Models; D008137:Longitudinal Studies; D016011:Normal Distribution