IDEAS home Printed from https://ideas.repec.org/a/sae/evarev/v7y1983i2p257-269.html
   My bibliography  Save this article

Categorizing Skewed, Limited Dependent Variables

Author

Listed:
  • Bengt Muthén

    (University of California, Los Angeles)

  • George Speckart

    (University of California, Los Angeles)

Abstract

Probit analysis is applied in a situation where analysis of covariance (ANCOVA) would customarily be used. The dichotomous dependent variables arise from dichotomizations of skewed continuous variables recorded as the proportion of time certain activities are observed. The probit approach avoids the biases of ordinary A NCO VA that arise due to skewness (limited variation). To illustrate this, data from 225 experiments and 214 control subjects in a drug treatment program was analyzed. It was found that the probit approach was able to reveal more substantial treatment effects than the ordinary A NCO VA.

Suggested Citation

  • Bengt Muthén & George Speckart, 1983. "Categorizing Skewed, Limited Dependent Variables," Evaluation Review, , vol. 7(2), pages 257-269, April.
    • Handle: RePEc:sae:evarev:v:7:y:1983:i:2:p:257-269
    DOI: 10.1177/0193841X8300700207
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0193841X8300700207
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0193841X8300700207?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:evarev:v:7:y:1983:i:2:p:257-269. 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.