title: Class Evolution Tree: a graphical tool to support decisions on the number of classes in exploratory categorical latent variable modeling for rehabilitation research.
abstract: The aim of our study was to develop a graphical tool that can be used in addition to standard statistical criteria to support decisions on the number of classes in explorative categorical latent variable modeling for rehabilitation research. Data from two rehabilitation research projects were used. In the first study, a latent profile analysis was carried out in patients with cancer receiving an inpatient rehabilitation program to identify prototypical combinations of treatment elements. In the second study, growth mixture modeling was used to identify latent trajectory classes based on weekly symptom severity measurements during inpatient treatment of patients with mental disorders. A graphical tool, the Class Evolution Tree, was developed, and its central components were described. The Class Evolution Tree can be used in addition to statistical criteria to systematically address the issue of number of classes in explorative categorical latent variable modeling.
authors.affiliation: Department of Medical Psychology, University Medical Center Hamburg-Eppendorf, Hamburg, Germany. l.kriston@uke.uni-hamburg.de
authors.forename: Levente
authors.initials: L
authors.lastname: Kriston
authors.forename: Hanne
authors.initials: H
authors.lastname: Melchior
authors.forename: Anika
authors.initials: A
authors.lastname: Hergert
authors.forename: Corinna
authors.initials: C
authors.lastname: Bergelt
authors.forename: Birgit
authors.initials: B
authors.lastname: Watzke
authors.forename: Holger
authors.initials: H
authors.lastname: Schulz
authors.forename: Alessa
authors.initials: A
authors.lastname: von Wolff
mesh_terms: D003131:Combined Modality Therapy; D003196:Computer Graphics; D003299:Cooperative Behavior; D003430:Cross-Sectional Studies; D003661:Decision Support Techniques; D003663:Decision Trees; D005858:Germany; D006302:Health Services Research / Q000706:statistics & numerical data; D006801:Humans; D033183:Interdisciplinary Communication; D008137:Longitudinal Studies; D001523:Mental Disorders / Q000534:rehabilitation*; D015233:Models, Statistical; D009369:Neoplasms / Q000534:rehabilitation*; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data; D010343:Patient Admission; D010348:Patient Care Team; D012046:Rehabilitation; D012047:Rehabilitation Centers; D012106:Research / Q000706:statistics & numerical data*