Statistical procedures for analyzing mental health services data.

Published

Journal Article (Review)

In mental health services research, analyzing service utilization data often poses serious problems, given the presence of substantially skewed data distributions. This article presents a non-technical introduction to statistical methods specifically designed to handle the complexly distributed datasets that represent mental health service use, including Poisson, negative binomial, zero-inflated, and zero-truncated regression models. A flowchart is provided to assist the investigator in selecting the most appropriate method. Finally, a dataset of mental health service use reported by medical patients is described, and a comparison of results across several different statistical methods is presented. Implications of matching data analytic techniques appropriately with the often complexly distributed datasets of mental health services utilization variables are discussed.

Full Text

Duke Authors

Cited Authors

  • Elhai, JD; Calhoun, PS; Ford, JD

Published Date

  • August 2008

Published In

Volume / Issue

  • 160 / 2

Start / End Page

  • 129 - 136

PubMed ID

  • 18585790

Pubmed Central ID

  • 18585790

Electronic International Standard Serial Number (EISSN)

  • 1872-7123

International Standard Serial Number (ISSN)

  • 0165-1781

Digital Object Identifier (DOI)

  • 10.1016/j.psychres.2007.07.003

Language

  • eng