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Inference for Survival Models with Doubly Interval Censored Data and Fixed or Time Dependent Covariate

In: Transactions on Engineering Technologies

Author

Listed:
  • Kaveh Kiani

    (Statistical Research and Training Center (SRTC), Data Processing and Dissemination Department)

  • Jayanthi Arasan

    (University Putra Malaysia, Faculty of Science, Department of Mathematics)

Abstract

In this research inference for survival models with doubly interval censored (DIC) data and fixed or time dependent covariate is discussed. DIC data usually arise in follow-up studies where the lifetime, T = W − V is the elapsed time between two related events, the first event, V and the second event, W where both events are interval censored (IC). The work starts by describing an algorithm that can be used to simulate doubly interval censored data. Following that the parameter estimates of two models with doubly interval censored data and either fixed or time dependent covariate is studied via a comprehensive simulation study. Finally the Wald and Jackknife confidence interval (CI) estimation procedures are explored for the parameters of the time dependent covariate model thorough a coverage probability study.

Suggested Citation

  • Kaveh Kiani & Jayanthi Arasan, 2019. "Inference for Survival Models with Doubly Interval Censored Data and Fixed or Time Dependent Covariate," Springer Books, in: Sio-Iong Ao & Len Gelman & Haeng Kon Kim (ed.), Transactions on Engineering Technologies, chapter 0, pages 187-203, Springer.
    • Handle: RePEc:spr:sprchp:978-981-32-9531-5_14
    DOI: 10.1007/978-981-32-9531-5_14
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