IDEAS home Printed from https://ideas.repec.org/a/bla/jorssc/v31y1982i2p144-148.html
   My bibliography  Save this article

Extra‐Binomial Variation in Logistic Linear Models

Author

Listed:
  • D. A. Williams

Abstract

The logistic‐linear model, and its maximum likelihood estimation by iterated reweighted least squares, can be simply modified to incorporate a component of extra‐binomial variation. The modifications are very easily effected if the GLIM program is used.

Suggested Citation

  • D. A. Williams, 1982. "Extra‐Binomial Variation in Logistic Linear Models," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 31(2), pages 144-148, June.
    • Handle: RePEc:bla:jorssc:v:31:y:1982:i:2:p:144-148
    DOI: 10.2307/2347977
    as

    Download full text from publisher

    File URL: https://doi.org/10.2307/2347977
    Download Restriction: no
    File URL: https://libkey.io/10.2307/2347977?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
    ---><---

    Citations

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


    Cited by:

    1. Maryam Aghayerashti & Ehsan Bahrami Samani & Mojtaba Ganjali, 2023. "Bayesian Latent Variable Model of Mixed Correlated Rank and Beta-Binomial Responses with Missing Data for the International Statistical Literacy Project Poster Competition," Sankhya B: The Indian Journal of Statistics, Springer;Indian Statistical Institute, vol. 85(1), pages 210-250, May.
    2. Richard B. Davies & Robert Crouchley, 1986. "The Mover-Stayer Model," Sociological Methods & Research, , vol. 14(4), pages 356-380, May.
    3. You-Gan Wang, 1999. "Estimating Equations for Removal Data Analysis," Biometrics, The International Biometric Society, vol. 55(4), pages 1263-1268, December.
    4. Roberto Patuelli & Daniel A. Griffith & Michael Tiefelsdorf & Peter Nijkamp, 2011. "Spatial Filtering and Eigenvector Stability: Space-Time Models for German Unemployment Data," International Regional Science Review, , vol. 34(2), pages 253-280, April.
    5. Garrett M. Fitzmaurice & John H. Goldthorpe, 1997. "Adjusting for Overdispersion in an Analysis of Comparative Social Mobility," Sociological Methods & Research, , vol. 25(3), pages 267-283, February.
    6. Chris J. Lloyd, 2000. "Regression Models for Convex ROC Curves," Biometrics, The International Biometric Society, vol. 56(3), pages 862-867, September.
    7. Christel Faes & Marc Aerts & Saskia Litière & Estelle Méroc & Yves Van der Stede & Koen Mintiens, 2011. "Estimating herd prevalence on the basis of aggregate testing of animals," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 174(1), pages 155-174, January.
    8. Erni Tri Astuti & Takashi Yanagawa, 2002. "Testing Trend for Count Data with Extra-Poisson Variability," Biometrics, The International Biometric Society, vol. 58(2), pages 398-402, June.
    9. Peter J. Hannan & David M. Murray, 1996. "Gauss or Bernoulli?," Evaluation Review, , vol. 20(3), pages 338-352, June.
    10. Francesca Dominici & Giovanni Parmigiani, 2001. "Bayesian Semiparametric Analysis of Developmental Toxicology Data," Biometrics, The International Biometric Society, vol. 57(1), pages 150-157, March.
    11. Peter Congdon, 1990. "Issues in the Analysis of Small Area Mortality," Urban Studies, Urban Studies Journal Limited, vol. 27(4), pages 519-536, August.
    12. Mabel Morales-Otero & Vicente Núñez-Antón, 2021. "Comparing Bayesian Spatial Conditional Overdispersion and the Besag–York–Mollié Models: Application to Infant Mortality Rates," Mathematics, MDPI, vol. 9(3), pages 1-33, January.
    13. Steve Leeds & Alan E. Gelfand, 1989. "Estimation for dirichlet mixed models," Naval Research Logistics (NRL), John Wiley & Sons, vol. 36(2), pages 197-214, April.
    14. Anwer S. Ahmed & Minsup Song & Douglas E. Stevens, 2009. "Earnings characteristics and analysts’ differential interpretation of earnings announcements: An empirical analysis," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 49(2), pages 223-246, June.
    15. Paul D. Allison, 1987. "Introducing a Disturbance into Logit and Probit Regression Models," Sociological Methods & Research, , vol. 15(4), pages 355-374, May.

    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:bla:jorssc:v:31:y:1982:i:2:p:144-148. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/rssssea.html .

    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.