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ERIC Number: EJ926510
Record Type: Journal
Publication Date: 2011-Jun
Pages: 5
Abstractor: As Provided
ISSN: ISSN-0342-5282
Class Evolution Tree: A Graphical Tool to Support Decisions on the Number of Classes in Exploratory Categorical Latent Variable Modeling for Rehabilitation Research
Kriston, Levente; Melchior, Hanne; Hergert, Anika; Bergelt, Corinna; Watzke, Birgit; Schulz, Holger; von Wolff, Alessa
International Journal of Rehabilitation Research, v34 n2 p181-185 Jun 2011
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.
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Publication Type: Journal Articles; Reports - Research
Education Level: N/A
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A