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Analyzing Repeated Measures on Generalized Linear Models via the Bootstrap

Lawrence H. Moulton and Scott L. Zeger
Biometrics
Vol. 45, No. 2 (Jun., 1989), pp. 381-394
DOI: 10.2307/2531484
Stable URL: http://www.jstor.org/stable/2531484
Page Count: 14
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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.
Analyzing Repeated Measures on Generalized Linear Models via the Bootstrap
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Abstract

The analysis of longitudinal data for which the response variables have nonnormal error distributions previously has been complex and/or dependent on restrictive assumptions. In this paper simple methods are introduced for the class of generalized linear models (GLMs). Regressions are fit to the data at each observation time; functions of the resulting coefficients may be bootstrapped, or the coefficients combined through closed-form estimation of their covariances. Application is made to a data set on xerophthalmia in Indonesian children.

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