Nonparametric mixture logistic regression models for clinical disposition

Chul W. Ahn, Juan E. Mezzich, Sunhee Ahn, Horacio Fabrega

Research output: Contribution to journalArticle

3 Citations (Scopus)

Abstract

Psychiatric hospitalization is one of the most important decisions in the care of patients. This is attributed to the complexity and intensity of treatment and isolation of patients from the family and community into a typically highly controlled and supervised setting. Logistic regression models are fitted to assess the relationship between DSM-III axes and psychiatric hospitalization decisions. Since the apparent error rate tends to underestimate the true error rate, the estimate for the downward bias of the apparent error was computed. A generalization of the logistic regression model is fitted where the intercept is assumed to be a random parameter.

Original languageEnglish (US)
Pages (from-to)23-33
Number of pages11
JournalJournal of Psychiatric Research
Volume28
Issue number1
DOIs
StatePublished - 1994

Fingerprint

Logistic Models
Psychiatry
Hospitalization
Patient Isolation
Diagnostic and Statistical Manual of Mental Disorders
Patient Care
Therapeutics

ASJC Scopus subject areas

  • Psychiatry and Mental health
  • Biological Psychiatry
  • Psychology(all)

Cite this

Nonparametric mixture logistic regression models for clinical disposition. / Ahn, Chul W.; Mezzich, Juan E.; Ahn, Sunhee; Fabrega, Horacio.

In: Journal of Psychiatric Research, Vol. 28, No. 1, 1994, p. 23-33.

Research output: Contribution to journalArticle

Ahn, Chul W. ; Mezzich, Juan E. ; Ahn, Sunhee ; Fabrega, Horacio. / Nonparametric mixture logistic regression models for clinical disposition. In: Journal of Psychiatric Research. 1994 ; Vol. 28, No. 1. pp. 23-33.
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