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On progressively censored competing risks data for Weibull distributions

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  • Pareek, Bhuvanesh
  • Kundu, Debasis
  • Kumar, Sumit

Abstract

In survival analysis, or in reliability study, an investigator is often interested in the assessment of a specific risk in the presence of other risk factors. It is well known as the competing risks problem in statistical literature. Moreover, censoring is inevitable in any life testing or reliability study. In this paper, we consider a very general censoring scheme, namely a progressive censoring scheme. It is further assumed that the lifetime distribution of the individual causes are independent and Weibull-distributed with the same shape parameters but different scale parameters. We obtain the maximum likelihood and approximate maximum likelihood estimates of the unknown parameters. We also compute the observed Fisher information matrix using the missing information principles, and use them to compute the asymptotic confidence intervals. Monte Carlo simulations are performed to compare the performances of the different methods, and one data set is analyzed for illustrative purposes. We also discuss different optimality criteria, and selected optimal progressive censoring plans are presented.

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  • Pareek, Bhuvanesh & Kundu, Debasis & Kumar, Sumit, 2009. "On progressively censored competing risks data for Weibull distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(12), pages 4083-4094, October.
    • Handle: RePEc:eee:csdana:v:53:y:2009:i:12:p:4083-4094
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    References listed on IDEAS

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    1. Ng, H. K. T. & Chan, P. S. & Balakrishnan, N., 2002. "Estimation of parameters from progressively censored data using EM algorithm," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 371-386, June.
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    5. Balakrishnan, N. & Kateri, M., 2008. "On the maximum likelihood estimation of parameters of Weibull distribution based on complete and censored data," Statistics & Probability Letters, Elsevier, vol. 78(17), pages 2971-2975, December.
    6. Balakrishnan, N. & Burkschat, Marco & Cramer, Erhard & Hofmann, Glenn, 2008. "Fisher information based progressive censoring plans," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 366-380, December.
    7. Erhard Cramer & Udo Kamps, 1996. "Sequential order statistics and k-out-of-n systems with sequentially adjusted failure rates," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 48(3), pages 535-549, September.
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    Cited by:

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    3. Hanan Haj Ahmad & Mohamed Aboshady & Mahmoud Mansour, 2024. "The Role of Risk Factors in System Performance: A Comprehensive Study with Adaptive Progressive Type-II Censoring," Mathematics, MDPI, vol. 12(11), pages 1-21, June.
    4. U. H. Salemi & S. Rezaei & Y. Si & S. Nadarajah, 2018. "On Optimal Progressive Censoring Schemes for Normal Distribution," Annals of Data Science, Springer, vol. 5(4), pages 637-658, December.
    5. Feizjavadian, S.H. & Hashemi, R., 2015. "Analysis of dependent competing risks in the presence of progressive hybrid censoring using Marshall–Olkin bivariate Weibull distribution," Computational Statistics & Data Analysis, Elsevier, vol. 82(C), pages 19-34.
    6. Muqrin A. Almuqrin & Mukhtar M. Salah & Essam A. Ahmed, 2022. "Statistical Inference for Competing Risks Model with Adaptive Progressively Type-II Censored Gompertz Life Data Using Industrial and Medical Applications," Mathematics, MDPI, vol. 10(22), pages 1-38, November.
    7. Wu, Shuo-Jye & Huang, Syuan-Rong, 2012. "Progressively first-failure censored reliability sampling plans with cost constraint," Computational Statistics & Data Analysis, Elsevier, vol. 56(6), pages 2018-2030.
    8. Mazen Nassar & Refah Alotaibi & Ahmed Elshahhat, 2023. "Reliability Estimation of XLindley Constant-Stress Partially Accelerated Life Tests using Progressively Censored Samples," Mathematics, MDPI, vol. 11(6), pages 1-24, March.
    9. Mazen Nassar & Refah Alotaibi & Chunfang Zhang, 2022. "Estimation of Reliability Indices for Alpha Power Exponential Distribution Based on Progressively Censored Competing Risks Data," Mathematics, MDPI, vol. 10(13), pages 1-25, June.
    10. Subhankar Dutta & Suchandan Kayal, 2023. "Inference of a competing risks model with partially observed failure causes under improved adaptive type-II progressive censoring," Journal of Risk and Reliability, , vol. 237(4), pages 765-780, August.
    11. Manoj Chacko & Rakhi Mohan, 2019. "Bayesian analysis of Weibull distribution based on progressive type-II censored competing risks data with binomial removals," Computational Statistics, Springer, vol. 34(1), pages 233-252, March.
    12. Jung-In Seo & Young Eun Jeon & Suk-Bok Kang, 2020. "New Approach for a Weibull Distribution under the Progressive Type-II Censoring Scheme," Mathematics, MDPI, vol. 8(10), pages 1-10, October.
    13. Cramer, Erhard & Schmiedt, Anja Bettina, 2011. "Progressively Type-II censored competing risks data from Lomax distributions," Computational Statistics & Data Analysis, Elsevier, vol. 55(3), pages 1285-1303, March.
    14. Jiaxin Nie & Wenhao Gui, 2019. "Parameter Estimation of Lindley Distribution Based on Progressive Type-II Censored Competing Risks Data with Binomial Removals," Mathematics, MDPI, vol. 7(7), pages 1-15, July.

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