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Full and conditional likelihood approaches for hazard change-point estimation with truncated and censored data

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  • Gürler, Ülkü
  • Deniz Yenigün, C.

Abstract

Hazard function plays an important role in reliability and survival analysis. In some real life applications, abrupt changes in the hazard function may be observed and it is of interest to detect the location and the size of the change. Hazard models with a change-point are considered when the observations are subject to random left truncation and right censoring. For a piecewise constant hazard function with a single change-point, two estimation methods based on the maximum likelihood ideas are considered. The first method assumes parametric families of distributions for the censoring and truncation variables, whereas the second one is based on conditional likelihood approaches. A simulation study is carried out to illustrate the performances of the proposed estimators. The results indicate that the fully parametric method performs better especially for estimating the size of the change, however the difference between the two methods vanish as the sample size increases. It is also observed that the full likelihood approach is not robust to model misspecification.

Suggested Citation

  • Gürler, Ülkü & Deniz Yenigün, C., 2011. "Full and conditional likelihood approaches for hazard change-point estimation with truncated and censored data," Computational Statistics & Data Analysis, Elsevier, vol. 55(10), pages 2856-2870, October.
    • Handle: RePEc:eee:csdana:v:55:y:2011:i:10:p:2856-2870
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    References listed on IDEAS

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    1. Pan, Wei & Chappell, Rick, 1998. "Computation of the NPMLE of distribution functions for interval censored and truncated data with applications to the Cox model," Computational Statistics & Data Analysis, Elsevier, vol. 28(1), pages 33-50, July.
    2. Sertkaya Karasoy, Durdu & Kadilar, Cem, 2007. "A new Bayes estimate of the change point in the hazard function," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2993-3001, March.
    3. Tuan Pham & Hung Nguyen, 1993. "Bootstrapping the change-point of a hazard rate," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 45(2), pages 331-340, June.
    4. Michael G. Hudgens & Glen A. Satten & Ira M. Longini, 2001. "Nonparametric Maximum Likelihood Estimation for Competing Risks Survival Data Subject to Interval Censoring and Truncation," Biometrics, The International Biometric Society, vol. 57(1), pages 74-80, March.
    5. Gijbels, I. & Wang, J. L., 1993. "Strong Representations of the Survival Function Estimator for Truncated and Censored Data with Applications," Journal of Multivariate Analysis, Elsevier, vol. 47(2), pages 210-229, November.
    6. Frobish, Daniel & Ebrahimi, Nader, 2009. "Parametric estimation of change-points for actual event data in recurrent events models," Computational Statistics & Data Analysis, Elsevier, vol. 53(3), pages 671-682, January.
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    Cited by:

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