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Observed and unobserved heterogeneity in failure data analysis

Author

Listed:
  • Rezgar Zaki
  • Abbas Barabadi
  • Javad Barabady
  • Ali Nouri Qarahasanlou

Abstract

In reality, failure data are often collected under diffract operational conditions (covariates), leading to heterogeneity among the data. Heterogeneity can be classified as observed and unobserved heterogeneity. Un-observed heterogeneity is the effect of unknown, unrecorded, or missing covariates. In most reliability studies, the effect of unobserved covariates is neglected. This may lead to inaccurate reliability modeling, and consequently, wrong operation and maintenance decisions. There is a lack of a systematic approach to model the unobserved covariate in reliability analysis. This paper aims to present a framework for reliability analysis in the presence of unobserved and observed covariates. Here, the unobserved covariates will be analyzed using frailty models. A case study will illustrate the application of the framework.

Suggested Citation

  • Rezgar Zaki & Abbas Barabadi & Javad Barabady & Ali Nouri Qarahasanlou, 2022. "Observed and unobserved heterogeneity in failure data analysis," Journal of Risk and Reliability, , vol. 236(1), pages 194-207, February.
    • Handle: RePEc:sae:risrel:v:236:y:2022:i:1:p:194-207
    DOI: 10.1177/1748006X211022538
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    References listed on IDEAS

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