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The Gamma-Frailty Poisson Model for the Nonparametric Estimation of Panel Count Data
Ying Zhang and Mortaza Jamshidian
Vol. 59, No. 4 (Dec., 2003), pp. 1099-1106
Published by: International Biometric Society
Stable URL: http://www.jstor.org/stable/3695351
Page Count: 8
You can always find the topics here!Topics: Simulations, Statistical estimation, Poisson process, Placebos, Urinary bladder neoplasms, Nonparametric models, Statistical models, Estimation methods, Sample size, Standard error
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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.
Biometrics © 2003 International Biometric Society