Characterizing persistent disturbing behavior using longitudinal and multivariate techniques

Jan Serroyen, Liesbeth Bruckers, Geert Rogiers, Geert Molenberghs*

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review


Persistent disturbing behavior (PDB) refers to a chronic condition in therapy-resistant psychiatric patients. Since these patients are highly unstable and difficult to maintain in their natural living environment and even in hospital wards, it is important to properly characterize this group. Previous studies in the Belgian province of Limburg indicated that the size of this group was larger than anticipated. Here, using a score calculated from longitudinal psychiatric registration data in 611 patients, we characterize the difference between PDB patients and a set of control patients. These differences are studied both at a given point in time, using discriminant analysis, as well as in terms of the evolution of the score over time, using longitudinal data analysis methods. Further, using clustering techniques, the group of PDB patients is split into two subgroups, characterized in terms of a number of ordinal scores. Such findings are useful from a scientific as well as from an organizational point of view.
Original languageEnglish
Pages (from-to)341-355
JournalJournal of Applied Statistics
Issue number2
Publication statusPublished - 2010


  • cluster analysis
  • discriminant analysis
  • longitudinal data
  • multivariate methods
  • psychiatry

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