Biometrics
journal article
A Random Effects Model for Binary Data
Mark R. Conaway
Biometrics
Vol. 46, No. 2 (Jun., 1990), pp. 317-328 (12 pages)
Published By: International Biometric Society
Biometrics
https://doi.org/10.2307/2531437
https://www.jstor.org/stable/2531437
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Abstract

This paper presents a method based on maximizing the marginal likelihood for analyzing binary data with random effects. With the assumption of a parametric family that allows for a wide variety of shapes for the distribution of the random effects, the marginal likelihood can be computed without numerical integrations. The method uses local independence models as well as those that incorporate additional dependence among the responses. Two examples, a panel study with binary responses and an analysis of item-response data, will be used to illustrate the method.

Journal Information

Biometrics is a scientific journal emphasizing the role of statistics and mathematics in the biological sciences. Its object is to promote and extend the use of mathematical and statistical methods in pure and applied biological sciences by describing developments in these methods and their applications in a form readily assimilable by experimental scientists. JSTOR provides a digital archive of the print version of Biometrics. The electronic version of Biometrics is available at http://www.blackwell-synergy.com/servlet/useragent?func=showIssues&code;=biom. Authorized users may be able to access the full text articles at this site.

Publisher Information

The International Biometric Society is an international society for the advancement of biological science through the development of quantitative theories and the application, development and dissemination of effective mathematical and statistical techniques. The Society welcomes as members biologists, mathematicians, statisticians, and others interested in applying similar techniques.

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Biometrics © 1990 International Biometric Society