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Panel Count Data Regression with Informative Observation Times

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  • Buzkova Petra

    (University of Washington)

Abstract

When patients are monitored for potentially recurrent events such as infections or tumor metastases, it is common for clinicians to ask patients to come back sooner for follow-ups based on the results of the most recent exam. This means that subjects' observation times will be irregular and related to subject-specific factors. Previously proposed methods for handling such panel count data assume that the dependence between the events process and the observation time process is governed by time-independent factors. This article considers situations where the observation times are predicted by time-varying factors such as the outcome observed at the last visit or cumulative exposure. Using a joint modelling approach, we propose a class of inverse-intensity-rate-ratio weighted estimators that are root-n consistent and asymptotically normal. The proposed estimators use estimating equations and are fairly simple and easy to compute. We demonstrate the performance of the method using simulated data and illustrate the approach using a cancer study dataset.

Suggested Citation

  • Buzkova Petra, 2010. "Panel Count Data Regression with Informative Observation Times," The International Journal of Biostatistics, De Gruyter, vol. 6(1), pages 1-24, September.
    • Handle: RePEc:bpj:ijbist:v:6:y:2010:i:1:n:30
    DOI: 10.2202/1557-4679.1239
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    References listed on IDEAS

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    1. 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.
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    Cited by:

    1. Li, Yang & Zhao, Hui & Sun, Jianguo & Kim, KyungMann, 2014. "Nonparametric tests for panel count data with unequal observation processes," Computational Statistics & Data Analysis, Elsevier, vol. 73(C), pages 103-111.
    2. Yayuan Zhu & Ziqi Chen & Jerald F. Lawless, 2022. "Semiparametric analysis of interval‐censored failure time data with outcome‐dependent observation schemes," Scandinavian Journal of Statistics, Danish Society for Theoretical Statistics;Finnish Statistical Society;Norwegian Statistical Association;Swedish Statistical Association, vol. 49(1), pages 236-264, March.
    3. Sy Han Chiou & Gongjun Xu & Jun Yan & Chiung‐Yu Huang, 2018. "Semiparametric estimation of the accelerated mean model with panel count data under informative examination times," Biometrics, The International Biometric Society, vol. 74(3), pages 944-953, September.

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