Semiparametric regression analysis of panel count data with informative observation times
This paper discusses regression analysis of panel count data that arise naturally when recurrent events are considered. For the analysis of panel count data, most of the existing methods have assumed that observation times are completely independent of recurrent events or given covariates, which may not be true in practice. We propose a joint modeling approach that uses an unobserved random variable and a completely unspecified link function to characterize the correlations between the response variable and the observation times. For inference about regression parameters, estimating equation approaches are developed without involving any estimation for latent variables, and the asymptotic properties of the resulting estimators are established. In addition, a technique is provided for assessing the adequacy of the model. The performance of the proposed estimation procedures are evaluated by means of Monte Carlo simulations, and a data set from a bladder tumor study is analyzed as an illustrative example.
If you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
As the access to this document is restricted, you may want to look for a different version under "Related research" (further below) or search for a different version of it.
References listed on IDEAS
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- Chiung-Yu Huang & Mei-Cheng Wang & Ying Zhang, 2006. "Analysing panel count data with informative observation times," Biometrika, Biometrika Trust, vol. 93(4), pages 763-775, December.
- Balakrishnan, N. & Zhao, Xingqiu, 2010. "A nonparametric test for the equality of counting processes with panel count data," Computational Statistics & Data Analysis, Elsevier, vol. 54(1), pages 135-142, January.
- Chiung-Yu Huang & Mei-Cheng Wang, 2004. "Joint Modeling and Estimation for Recurrent Event Processes and Failure Time Data," Journal of the American Statistical Association, American Statistical Association, vol. 99, pages 1153-1165, December.
- J. Sun & L. J. Wei, 2000. "Regression analysis of panel count data with covariate-dependent observation and censoring times," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(2), pages 293-302.
- Jianguo Sun, 2003. "A nonparametric test for panel count data," Biometrika, Biometrika Trust, vol. 90(1), pages 199-208, March.
- Minggen Lu & Ying Zhang & Jian Huang, 2007. "Estimation of the mean function with panel count data using monotone polynomial splines," Biometrika, Biometrika Trust, vol. 94(3), pages 705-718.
- Ying Zhang, 2006. "Nonparametric k-sample tests with panel count data," Biometrika, Biometrika Trust, vol. 93(4), pages 777-790, December.
- D. Y. Lin & L. J. Wei & I. Yang & Z. Ying, 2000. "Semiparametric regression for the mean and rate functions of recurrent events," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 62(4), pages 711-730.
- Ying Zhang, 2002. "A semiparametric pseudolikelihood estimation method for panel count data," Biometrika, Biometrika Trust, vol. 89(1), pages 39-48, March.
- Wang M-C. & Qin J. & Chiang C-T., 2001. "Analyzing Recurrent Event Data With Informative Censoring," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 1057-1065, September.
- X. Joan Hu & Jianguo Sun & Lee-Jen Wei, 2003. "Regression Parameter Estimation from Panel Counts," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 30(1), pages 25-43.
- Lin D Y & Ying Z, 2001. "Semiparametric and Nonparametric Regression Analysis of Longitudinal Data," Journal of the American Statistical Association, American Statistical Association, vol. 96, pages 103-126, March.
When requesting a correction, please mention this item's handle: RePEc:eee:csdana:v:55:y:2011:i:1:p:291-300. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei)
If references are entirely missing, you can add them using this form.