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Regression Analysis of Longitudinal Data in the Presence of Informative Observation and Censoring Times

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  • Sun, Jianguo
  • Sun, Liuquan
  • Liu, Dandan

Abstract

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  • Sun, Jianguo & Sun, Liuquan & Liu, Dandan, 2007. "Regression Analysis of Longitudinal Data in the Presence of Informative Observation and Censoring Times," Journal of the American Statistical Association, American Statistical Association, vol. 102, pages 1397-1406, December.
    • Handle: RePEc:bes:jnlasa:v:102:y:2007:m:december:p:1397-1406
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    Citations

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    Cited by:

    1. Sun, Liuquan & Tong, Xingwei, 2009. "Analyzing longitudinal data with informative observation times under biased sampling," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1162-1168, May.
    2. Peter McCullagh, 2008. "Sampling bias and logistic models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 643-677, September.
    3. Na Cai & Wenbin Lu & Hao Helen Zhang, 2012. "Time-Varying Latent Effect Model for Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 68(4), pages 1093-1102, December.
    4. Charles E. McCulloch & John M. Neuhaus & Rebecca L. Olin, 2016. "Biased and unbiased estimation in longitudinal studies with informative visit processes," Biometrics, The International Biometric Society, vol. 72(4), pages 1315-1324, December.
    5. Sun, Dayu & Zhao, Hui & Sun, Jianguo, 2021. "Regression analysis of asynchronous longitudinal data with informative observation processes," Computational Statistics & Data Analysis, Elsevier, vol. 157(C).
    6. Deng, Shirong & Liu, Kin-yat & Zhao, Xingqiu, 2017. "Semiparametric regression analysis of multivariate longitudinal data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 107(C), pages 120-130.
    7. Yang, Guangren & Zhou, Yong, 2014. "Semiparametric varying-coefficient study of mean residual life models," Journal of Multivariate Analysis, Elsevier, vol. 128(C), pages 226-238.
    8. Caleb Weaver & Luo Xiao & Wenbin Lu, 2023. "Functional data analysis for longitudinal data with informative observation times," Biometrics, The International Biometric Society, vol. 79(2), pages 722-733, June.
    9. Qing Cai & Mei‐Cheng Wang & Kwun Chuen Gary Chan, 2017. "Joint modeling of longitudinal, recurrent events and failure time data for survivor's population," Biometrics, The International Biometric Society, vol. 73(4), pages 1150-1160, December.
    10. Zhao, Xingqiu & Tong, Xingwei & Sun, Jianguo, 2013. "Robust estimation for panel count data with informative observation times," Computational Statistics & Data Analysis, Elsevier, vol. 57(1), pages 33-40.
    11. Lianqiang Qu & Liuquan Sun & Xinyuan Song, 2018. "A Joint Modeling Approach for Longitudinal Data with Informative Observation Times and a Terminal Event," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 10(3), pages 609-633, December.
    12. Yu Liang & Wenbin Lu & Zhiliang Ying, 2009. "Joint Modeling and Analysis of Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 65(2), pages 377-384, June.
    13. Liang Li & Sheng Luo & Bo Hu & Tom Greene, 2017. "Dynamic Prediction of Renal Failure Using Longitudinal Biomarkers in a Cohort Study of Chronic Kidney Disease," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 9(2), pages 357-378, December.
    14. Zhou, Jie & Song, Xinyuan & Sun, Liuquan, 2020. "Continuous time hidden Markov model for longitudinal data," Journal of Multivariate Analysis, Elsevier, vol. 179(C).

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