NDLI: Predicting outcomes of inpatient psychotherapy using quality management data: comparing classification and regression trees with logistic regression and linear discriminant analysis.

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Predicting outcomes of inpatient psychotherapy using quality management data: comparing classification and regression trees with logistic regression and linear discriminant analysis.

Content Provider	World Health Organization (WHO)-Global Index Medicus
Author	Hannöver, Wolfgang Kordy, Hans
Description	Author Affiliation: Hannöver W ( a Institute for Medical Psychology , Ernst-Moritz-Arndt-University and Center for Psychotherapy Research , Stuttgart.)
Abstract	Abstract Three classification models are compared with regard to their ability to identify unsuccessful treatment outcomes. Data from the Stuttgart-Heidelberg model on quality management of 1,401 inpatients were used. According to the evaluation algorithm used, 82% benefited from therapy. Outcomes were classified using logistic regression, linear discriminant analysis, and classification and regression trees. For the regression techniques, variables were selected stepwise backward; for the CART model, the method-inherent selection scheme was adopted. Because there were few signal cases in the data, these cases were double weighted. Model performance was obtained using classic cross-validation. Overall misclassification rates did not differ between methods for the construction sample but differed when applied to the validation sample. Overall classification rates for the given problem are modest.
File Format	HTM / HTML
ISSN	10503307
Issue Number	3
Journal	Psychotherapy Research
Volume Number	15
e-ISSN	14684381
Language	English
Publisher	Taylor & Francis
Publisher Date	2005-07-01
Publisher Place	Great Britain (UK)
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Discipline Psychiatry Discipline Therapeutics Discipline Psychology
Content Type	Text
Resource Type	Article
Subject	Clinical Psychology

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