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Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/8967

Title: Classification methods multi-class multivariate longitudinal data
Authors: Wouters, Kristien
Advisors: Molenberghs, Geert
Cortinas Abrahantes, Jose
Issue Date: 2008
Publisher: UHasselt Diepenbeek
Abstract: In this thesis, we have focussed on the classification of multiple class, multivariate longitudinal data. This research was driven by a study conducted to classify psychotropic drugs based on electro-encephalogram or EEG data. For each of the compound-by-dose combinations in the five psychotropic drug classes, data on the sleep-wake behaviour of rats were collected during a 16 hours period. The sleepwake behaviour was summarized into six standard sleep-wake stages, resulting in a six-variate longitudinal profile per rat. From a statistical point of view, analyzing EEG data poses important challenge, because of the high-dimensionality and the longitudinal character of the data. The longitudinal profiles are usually highly irregular and the variability between and within subjects are relatively high.
URI: http://hdl.handle.net/1942/8967
Category: T1
Type: Theses and Dissertations
Appears in Collections: PhD theses
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