A nonparametric time-varying coefficient model for panel count data

Huadong Zhao, Wanzhu Tu, Zhangsheng Yu

Research output: Contribution to journalArticle

1 Citation (Scopus)

Abstract

In this research, we describe a nonparametric time-varying coefficient model for the analysis of panel count data. We extend the traditional panel count data models by incorporating B-splines estimates of time-varying coefficients. We show that the proposed model can be implemented using a nonparametric maximum pseudo-likelihood method. We further examine the theoretical properties of the estimators of model parameters. The operational characteristics of the proposed method are evaluated through a simulation study. For illustration, we analyse data from a study of childhood wheezing, and describe the time-varying effect of an inflammatory marker on the risk of wheezing.

Original languageEnglish (US)
Pages (from-to)1-22
Number of pages22
JournalJournal of Nonparametric Statistics
DOIs
StateAccepted/In press - Apr 14 2018

Fingerprint

Time-varying Coefficients
Varying Coefficient Model
Count Data
Panel Data
Likelihood Methods
B-spline
Data Model
Time-varying
Simulation Study
Estimator
Model
Estimate
Time-varying coefficient model
Count data
Pseudo-likelihood
Time-varying coefficients
Count data models
Childhood
Simulation study

Keywords

  • B-splines
  • panel count data
  • time-varying coefficients

ASJC Scopus subject areas

  • Statistics and Probability
  • Statistics, Probability and Uncertainty

Cite this

A nonparametric time-varying coefficient model for panel count data. / Zhao, Huadong; Tu, Wanzhu; Yu, Zhangsheng.

In: Journal of Nonparametric Statistics, 14.04.2018, p. 1-22.

Research output: Contribution to journalArticle

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