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Latent Class Analysis of Anxiety and Depression

Bibliographic Data

ID2331643
AuthorsW W Eaton (0000-0002-2776-7258, Johns Hopkins University), Allan L Mccutcheon (University of Delaware), Allan Mccutcheon (University of Delaware), Amy Dryman (Johns Hopkins University), Ann Sorenson (University of Toronto), Ann W Sorenson (University of Toronto)
Year1989
Volume18
Issue1
Pages104-125
Publication date1989-08-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueSociological Methods & Research (JOURNAL)
Journal identifiersISSN: 0049-1241 • E-ISSN: 1552-8294
PublisherSAGE Publications Inc (PUBLISHER)
DOI10.1177/0049124189018001004
OpenAlexW2038930641
LanguageEN
Citations received4
References cited5

This article applies the technique of Latent Class Analysis to data on 41 symptoms of anxiety and depression from the Baltimore and Durham sites of the Epidemiologic Catchment Area Program. An exploratory analysis on the Baltimore data fit three latent classes, which were then replicated on the Durham data. An analysis of Dysphoria and eight symptom groups related to depression revealed a close fit between the DSM-III configuration of Major Depressive Disorder and one of three latent classes

Anxiety · Class (philosophy) · Data science · Depression (economics) · Dysphoria · Exploratory analysis · Latent class model · Psychiatry · Statistics · Clinical Psychology · Computer Science · Health disparities and outcomes · Mathematics · Psychology · Statistical Methods and Bayesian Inference

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Unique citing works4
Citations per year0,15
Citation span1999 - 2022 (24)
Citation velocityhistorical
Highly citedNo
Citation typesNeutral: 4

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