title: A robust mixed linear model analysis for longitudinal data.
abstract: This paper describes robust procedures for estimating parameters of a mixed effects linear model as applied to longitudinal data. In addition to fixed regression parameters, the model incorporates random subject effects to accommodate between-subjects variability and autocorrelation for within-subject variability. Robust empirical Bayesian estimation of subject effects is briefly discussed. As an illustration, the procedures are applied to data from a multiple sclerosis clinical trial.
authors.affiliation: Department of Mathematics and Statistics, Okanagan University College, Kelowna BC, Canada. pgill@okanagan.bc.ca
authors.forename: P S
authors.initials: PS
authors.lastname: Gill
mesh_terms: D000276:Adjuvants, Immunologic / Q000008:administration & dosage; D001499:Bayes Theorem; D015331:Cohort Studies; D006801:Humans; D016899:Interferon-beta / Q000008:administration & dosage; D016014:Linear Models; D008137:Longitudinal Studies; D009103:Multiple Sclerosis / Q000188:drug therapy; D016032:Randomized Controlled Trials as Topic
chemical_list: D000276:Adjuvants, Immunologic; D016899:Interferon-beta