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A Mixed-Effects Model for Categorical Data

Paula J. Beitler and J. Richard Landis
Biometrics
Vol. 41, No. 4 (Dec., 1985), pp. 991-1000
DOI: 10.2307/2530970
Stable URL: http://www.jstor.org/stable/2530970
Page Count: 10
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Since scans are not currently available to screen readers, please contact JSTOR User Support for access. We'll provide a PDF copy for your screen reader.
A Mixed-Effects Model for Categorical Data
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Abstract

A mixed model for categorical data from unbalanced designs which is directly analogous to a two-way ANOVA model for quantitative data is proposed. An extension of the fitting constants method is developed to estimate model variance components based on appropriate reductions in sums of squares. The resulting variance component estimators are incorporated into the covariance structure of a general linear models Wald statistic to test for treatment differences. These procedures are illustrated with data obtained from a multicenter clinical trial in which the treatments are regarded as fixed effects and the clinics are regarded as random effects.

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