IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v18y1989i1p104-125.html
   My bibliography  Save this article

Latent Class Analysis of Anxiety and Depression

Author

Listed:
  • WILLIAM W. EATON

    (Johns Hopkins University)

  • ALLAN McCUTCHEON

    (University of Delaware)

  • AMY DRYMAN

    (Johns Hopkins University)

  • ANN SORENSON

    (University of Toronto)

Abstract

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.

Suggested Citation

  • WILLIAM W. EATON & ALLAN McCUTCHEON & AMY DRYMAN & ANN SORENSON, 1989. "Latent Class Analysis of Anxiety and Depression," Sociological Methods & Research, , vol. 18(1), pages 104-125, August.
  • Handle: RePEc:sae:somere:v:18:y:1989:i:1:p:104-125
    DOI: 10.1177/0049124189018001004
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124189018001004
    Download Restriction: no

    File URL: https://libkey.io/10.1177/0049124189018001004?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:somere:v:18:y:1989:i:1:p:104-125. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.