IDEAS home Printed from https://ideas.repec.org/a/sae/somere/v18y1989i1p66-103.html
   My bibliography  Save this article

An Application of the Item-Response Model to Psychiatric Epidemiology

Author

Listed:
  • MARK REISER

    (Arizona State University)

Abstract

This article presents the item-response model and an application of the model to variables representing symptoms of anxiety and depression. The model is presented as having features in common with a multivariate logistic regression where the independent variable is continuous, real-valued, and unobservable. Some connections to dichotomous variable factor analysis and the latent class model are also discussed. In the application, data are used from the National Institute of Mental Health Epidemiologic Catchment Area Survey. The model is most successful with symptoms of anxiety, where the variables are small in number and satisfy the assumption of unidimensionality. It is less successful with the symptoms of major depressive disorder, where the unidimensionality does not seem to hold.

Suggested Citation

  • Mark Reiser, 1989. "An Application of the Item-Response Model to Psychiatric Epidemiology," Sociological Methods & Research, , vol. 18(1), pages 66-103, August.
    • Handle: RePEc:sae:somere:v:18:y:1989:i:1:p:66-103
    DOI: 10.1177/0049124189018001003
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0049124189018001003
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0049124189018001003?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
    ---><---

    References listed on IDEAS

    as
    1. Steven Rigdon & Robert Tsutakawa, 1983. "Parameter estimation in latent trait models," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 567-574, December.
    2. R. Bock & Murray Aitkin, 1981. "Marginal maximum likelihood estimation of item parameters: Application of an EM algorithm," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 443-459, December.
    3. R. Darrell Bock, 1972. "Estimating item parameters and latent ability when responses are scored in two or more nominal categories," Psychometrika, Springer;The Psychometric Society, vol. 37(1), pages 29-51, March.
    4. Frederic Lord, 1953. "An application of confidence intervals and of maximum likelihood to the estimation of an examinee's ability," Psychometrika, Springer;The Psychometric Society, vol. 18(1), pages 57-76, March.
    5. Bengt Muthén & Anders Christoffersson, 1981. "Simultaneous factor analysis of dichotomous variables in several groups," Psychometrika, Springer;The Psychometric Society, vol. 46(4), pages 407-419, December.
    6. Anders Christoffersson, 1975. "Factor analysis of dichotomized variables," Psychometrika, Springer;The Psychometric Society, vol. 40(1), pages 5-32, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. repec:jss:jstsof:25:i08 is not listed on IDEAS

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Yoshio Takane & Jan Leeuw, 1987. "On the relationship between item response theory and factor analysis of discretized variables," Psychometrika, Springer;The Psychometric Society, vol. 52(3), pages 393-408, September.
    2. Dylan Molenaar, 2015. "Heteroscedastic Latent Trait Models for Dichotomous Data," Psychometrika, Springer;The Psychometric Society, vol. 80(3), pages 625-644, September.
    3. Albert Maydeu-Olivares & Harry Joe, 2006. "Limited Information Goodness-of-fit Testing in Multidimensional Contingency Tables," Psychometrika, Springer;The Psychometric Society, vol. 71(4), pages 713-732, December.
    4. Alberto Maydeu-Olivares & Rosa Montaño, 2013. "How Should We Assess the Fit of Rasch-Type Models? Approximating the Power of Goodness-of-Fit Statistics in Categorical Data Analysis," Psychometrika, Springer;The Psychometric Society, vol. 78(1), pages 116-133, January.
    5. Cafarelli Ryan & Rigdon Christopher J. & Rigdon Steven E., 2012. "Models for Third Down Conversion in the National Football League," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 8(3), pages 1-26, October.
    6. Björn Andersson & Tao Xin, 2021. "Estimation of Latent Regression Item Response Theory Models Using a Second-Order Laplace Approximation," Journal of Educational and Behavioral Statistics, , vol. 46(2), pages 244-265, April.
    7. Cees Glas, 1988. "The derivation of some tests for the rasch model from the multinomial distribution," Psychometrika, Springer;The Psychometric Society, vol. 53(4), pages 525-546, December.
    8. Javier Revuelta, 2004. "Analysis of distractor difficulty in multiple-choice items," Psychometrika, Springer;The Psychometric Society, vol. 69(2), pages 217-234, June.
    9. Alexander Robitzsch, 2024. "A Comparison of Limited Information Estimation Methods for the Two-Parameter Normal-Ogive Model with Locally Dependent Items," Stats, MDPI, vol. 7(3), pages 1-16, June.
    10. Ulf Böckenholt, 2012. "The Cognitive-Miser Response Model: Testing for Intuitive and Deliberate Reasoning," Psychometrika, Springer;The Psychometric Society, vol. 77(2), pages 388-399, April.
    11. Albert Yu & Jeffrey A. Douglas, 2023. "IRT Models for Learning With Item-Specific Learning Parameters," Journal of Educational and Behavioral Statistics, , vol. 48(6), pages 866-888, December.
    12. Wu, Jianmin & Bentler, Peter M., 2013. "Limited information estimation in binary factor analysis: A review and extension," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 392-403.
    13. Yang Liu & Jan Hannig, 2017. "Generalized Fiducial Inference for Logistic Graded Response Models," Psychometrika, Springer;The Psychometric Society, vol. 82(4), pages 1097-1125, December.
    14. Salim Moussa, 2016. "A two-step item response theory procedure for a better measurement of marketing constructs," Journal of Marketing Analytics, Palgrave Macmillan, vol. 4(1), pages 28-50, March.
    15. Ogasawara, Haruhiko, 2013. "Asymptotic cumulants of ability estimators using fallible item parameters," Journal of Multivariate Analysis, Elsevier, vol. 119(C), pages 144-162.
    16. Yang Liu & Weimeng Wang, 2022. "Semiparametric Factor Analysis for Item-Level Response Time Data," Psychometrika, Springer;The Psychometric Society, vol. 87(2), pages 666-692, June.
    17. Robert Mislevy, 1991. "Randomization-based inference about latent variables from complex samples," Psychometrika, Springer;The Psychometric Society, vol. 56(2), pages 177-196, June.
    18. Barry V. Bye & Salvatore J. Gallicchio & Janice M. Dykacz, 1985. "Multiple-Indicator, Multiple-Cause Models for a Single Latent Variable with Ordinal Indicators," Sociological Methods & Research, , vol. 13(4), pages 487-509, May.
    19. Ji Seung Yang & Xiaying Zheng, 2018. "Item Response Data Analysis Using Stata Item Response Theory Package," Journal of Educational and Behavioral Statistics, , vol. 43(1), pages 116-129, February.
    20. Singh, Jagdip, 2004. "Tackling measurement problems with Item Response Theory: Principles, characteristics, and assessment, with an illustrative example," Journal of Business Research, Elsevier, vol. 57(2), pages 184-208, February.

    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:66-103. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.