Latent class analysis of persistent disturbing behaviour patients by using longitudinal profiles

Liesbeth Bruckers*, Jan Serroyen, Geert Molenberghs, Herman Slaets, Willem Goeyvaerts

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

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Abstract

Summary. Persistent disturbing behaviour refers to a chronic condition in highly unstable, therapy resistant psychiatric patients. Because these patients are difficult to maintain in their natural living environment and even in hospital wards, purposely designed residential psychiatric facilities need to be established. Therefore, it is important to define and circumscribe the group carefully. Serroyen and co-workers, starting from the longitudinal analysis of a score based on data from the belgian national psychiatric registry, undertook a discriminant analysis to distinguish persistent disturbing behaviour patients from a control group. They also indicated that there is scope for further subdividing the persistent disturbing behaviour patients into two subgroups, using conventional cluster analysis techniques. We employ a variety of novel longitudinal-data-based cluster analysis techniques. These are based on either conventional growth models, growth–mixture models or latent class growth models. Unlike in earlier analyses, where some evidence for two groups was found, there now is an indication of three groups, which is a finding with high practical and organizational relevance.
Original languageEnglish
Pages (from-to)495-512
JournalJournal of the Royal Statistical Society Series C-Applied Statistics
Volume59
DOIs
Publication statusPublished - 2010

Keywords

  • Growth curves
  • Growth mixture models
  • Latent class growth models
  • Linear mixed models

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