A Nonparametric Estimator of Bivariate Quantile Residual Life Model with Application to Tumor Recurrence Data Set

Kayid, Mohamed; Noughabi, M. Shafaei; Abouammoh, A. M.

doi:10.1007/s00357-018-9300-z

Cited by 5 publications

(3 citation statements)

References 22 publications

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“…However, it is not trivial to extend this prediction method under competing risks. This risk prediction scheme is equivalent to dynamic prediction [48][49][50][51][52][53]. Moreover, the accelerated life test plans may be considered including the case of one-shot devices with competing risks [54,55].…”

Section: Discussionmentioning

confidence: 99%

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Michimae

Emura

2022

Mathematics

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Survival and reliability analyses deal with incomplete failure time data, such as censored and truncated data. Recently, the classical left-truncation scheme was generalized to analyze “field data”, defined as samples collected within a fixed period. However, existing competing risks models dealing with left-truncated field data are not flexible enough. We propose copula-based competing risks models for latent failure times, permitting a flexible parametric form. We formulate maximum likelihood estimation methods under the Weibull, lognormal, and gamma distributions for the latent failure times. We conduct simulations to check the performance of the proposed methods. We finally give a real data example. We provide the R code to reproduce the simulations and data analysis results.

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Section: Discussionmentioning

confidence: 99%

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Michimae

Emura

2022

Mathematics

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“…This risk prediction scheme is essentially equivalent to the dynamic risk prediction [48][49][50][51] and residual lifetime prediction. 52,53 F I G U R E 2 Predicted failure probabilities in use at 𝑡 = 10 (years) and 𝑡 = 30 (years)…”

Section: Lifetime Predictionmentioning

confidence: 99%

“…This risk assessment at a certain point of time may be informative for engineers to make decisions on future maintenance or repair. This risk prediction scheme is essentially equivalent to the dynamic risk prediction 48–51 and residual lifetime prediction 52,53 …”

Section: Lifetime Predictionmentioning

confidence: 99%

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Emura

Michimae

2022

Quality & Reliability Eng

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In field reliability analyses, a data collection period is given to monitor the failure events from the field. Left‐truncation arises due to early failures occurring before the data collection period, and right‐censoring arises for late failures occurring beyond the monitoring period. Naïve analyses of left‐truncated and right‐censored data lead to biased estimation of the population lifetime of interest. A variety of models and methods have been developed to analyze the left‐truncated and right‐censored data for field reliability analyses. The goal of the paper is to review the existing models and methods for fitting left‐truncated and right‐censored data. Our review includes the existing statistical models, such as the exponential, Weibull, lognormal, gamma, Gompertz, Lomax, and spline models. We comprehensively review the statistical issues of maximum likelihood estimation, model selection, residual lifetime prediction, and Bayesian methods. Some of these methods are illustrated through the field reliability analysis of the electric power transformer dataset.

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Quantiles of the conditional residual lifetime

2021

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A Nonparametric Estimator of Bivariate Quantile Residual Life Model with Application to Tumor Recurrence Data Set

Cited by 5 publications

References 22 publications

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Likelihood Inference for Copula Models Based on Left-Truncated and Competing Risks Data from Field Studies

Left‐truncated and right‐censored field failure data: Review of parametric analysis for reliability

Quantiles of the conditional residual lifetime

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