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Marginal analysis of panel counts through estimating functions

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  • X. Joan Hu
  • Stephen W. Lagakos
  • Richard A. Lockhart

Abstract

We develop nonparametric estimation procedures for the marginal mean function of a counting process based on periodic observations, using two types of self-consistent estimating equations. The first is derived from the likelihood studied by Wellner & Zhang (2000), assuming a Poisson counting process. It gives a nondecreasing estimator, which equals the nonparametric maximum likelihood estimator of Wellner & Zhang and is consistent without the Poisson assumption. Motivated by the construction of parametric generalized estimating equations, the second type is a set of data-adaptive quasi-score functions, which are likelihood estimating functions under a mixed-Poisson assumption. We evaluate the procedures using simulation, and illustrate them with the data from a bladder cancer study. Copyright 2009, Oxford University Press.

Suggested Citation

  • X. Joan Hu & Stephen W. Lagakos & Richard A. Lockhart, 2009. "Marginal analysis of panel counts through estimating functions," Biometrika, Biometrika Trust, vol. 96(2), pages 445-456.
    • Handle: RePEc:oup:biomet:v:96:y:2009:i:2:p:445-456
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    File URL: http://hdl.handle.net/10.1093/biomet/asp010
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    Cited by:

    1. Zhao, Hui & Sun, Dayu & Li, Gang & Sun, Jianguo, 2019. "Simultaneous estimation and variable selection for incomplete event history studies," Journal of Multivariate Analysis, Elsevier, vol. 171(C), pages 350-361.
    2. C. Dean & E. Juarez Colunga, 2011. "Comments on: Nonparametric inference based on panel count data," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 20(1), pages 43-45, May.
    3. Gang Cheng & Ying Zhang & Liqiang Lu, 2011. "Efficient algorithms for computing the non and semi-parametric maximum likelihood estimates with panel count data," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(2), pages 567-579.

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