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The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data

Ying Zhang and Mortaza Jamshidian
Biometrics
Vol. 59, No. 4 (Dec., 2003), pp. 1099-1106
Stable URL: http://www.jstor.org/stable/3695351
Page Count: 8
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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.
The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data
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Abstract

In this article, we study nonparametric estimation of the mean function of a counting process with panel observations. We introduce the gamma frailty variable to account for the intracorrelation between the panel counts of the counting process and construct a maximum pseudo-likelihood estimate with the frailty variable. Three simulated examples are given to show that this estimation procedure, while preserving the robustness and simplicity of the computation, improves the efficiency of the nonparametric maximum pseudo-likelihood estimate studied in Wellner and Zhang (2000, Annals of Statistics 28, 779-814). A real example from a bladder tumor study is used to illustrate the method.

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