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Activity Number: 182
Type: Contributed
Date/Time: Monday, August 1, 2016 : 10:30 AM to 12:20 PM
Sponsor: IMS
Abstract #320272 View Presentation
Title: A Nonparametric Regression Model for Panel Count Data Analysis
Author(s): Huadong Zhao*
Companies: East China Normal University
Keywords: Childhood wheezing ; Empirical process ; pseudolikelihood estimator ; Regression splines
Abstract:

Panel count data are commonly encountered in analysis of recurrent events where the exact event occurrence times are unobserved. To accommodate the potential non-linear covariate effect, we consider a nonparametric regression model for panel count data. Regression B-splines method is used to estimate the regression functions and the baseline mean function as well. The B-splines based estimation is shown to be consistent and achieve the optimal rate for convergence. Moreover, asymptotic normality for regression splines estimators is also establihed. Numerical studies are carried out to justify the finite sample properties. Final, we apply the proposed method to analyze the non-linear effect of the lung function on the risks of childhood wheezing.


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