Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/31092 
Year of Publication: 
2003
Series/Report no.: 
Discussion Paper No. 353
Publisher: 
Ludwig-Maximilians-Universität München, Sonderforschungsbereich 386 - Statistische Analyse diskreter Strukturen, München
Abstract: 
This paper aims at proposing suitable statistical tools to address heterogeneity in repeated measures, within a Multiple Sclerosis (MS) longitudinal study. Indeed, due to unobservable sources of heterogeneity, modelling the effect of covariates on MS severity evolves as a very difficult feature. Bayesian P-Splines are suggested for modelling non linear smooth effects of covariates within generalized additive models. Thus, based on a pooled MS data set, we show how extending bayesian P-splines (Lang and Brezger, 2001) to mixed effects models, represents an attractive statistical approach to investigate the role of prognostic factors in affecting individual change in disability.
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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