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Identifiability of masking probabilities in competing risks models with emphasis on Weibull models

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  • Ye Liang
  • Dongchu Sun

Abstract

Lifetime data with masked failure causes arise in both reliability engineering and epidemiology. The phenomenon of masking occurs when a subject is exposed to multiple risks. A competing risks model with masking probabilities is widely used for the masked failure data. However, in many cases, the model suffers from an identification problem. We show that the identifiability of masking probabilities depends on both the structure of data and the cause-specific hazard functions. Motivated by this result, two existing solutions are reviewed and further improved.

Suggested Citation

  • Ye Liang & Dongchu Sun, 2016. "Identifiability of masking probabilities in competing risks models with emphasis on Weibull models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(7), pages 2143-2157, April.
  • Handle: RePEc:taf:lstaxx:v:45:y:2016:i:7:p:2143-2157
    DOI: 10.1080/03610926.2013.878358
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    Cited by:

    1. Jing Cai & Yimin Shi & Bin Liu, 2017. "Statistical analysis for masked system life data from Marshall‐Olkin Weibull distribution under progressive hybrid censoring," Naval Research Logistics (NRL), John Wiley & Sons, vol. 64(6), pages 490-501, September.

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