Multivariate failure time distributions derived from shared frailty and copulas

Wang, Yin-Chen; Emura, Takeshi

doi:10.1007/s42081-021-00123-1

Cited by 9 publications

(2 citation statements)

References 54 publications

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“…The review of parametric regression models in survival and reliability is a potential topic for further investigation. Moreover, many real data include multivariate survival outcomes, recurrent events, dependent censoring, and competing risks [5,6,8,9,44,49,50,61,121,[141][142][143][144][145]. The state-of-the art review of multivariate survival distributions and competing risk models is an important topic for further investigation.…”

Section: Discussionmentioning

confidence: 99%

Parametric Distributions for Survival and Reliability Analyses, a Review and Historical Sketch

et al. 2022

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During its 330 years of history, parametric distributions have been useful for survival and reliability analyses. In this paper, we comprehensively review the historical backgrounds and statistical properties of a number of parametric distributions used in survival and reliability analyses. We provide encyclopedic coverage of the important parametric distributions, which is more extensive than the existing textbooks on survival and reliability analyses. We also explain how these distributions have been adopted in survival and reliability analyses with original and state-of-the-art references. We cover the exponential, Weibull, Rayleigh, lognormal, log-logistic, gamma, generalized gamma, Pareto (types I, II, and IV), Hjorth, Burr (types III and XII), Dagum, exponential power, Gompertz, Birnbaum-Saunders, exponential-logarithmic, piecewise exponential, generalized exponential, exponentiated Weibull, generalized modified Weibull, and spline distributions. We analyze a real dataset for illustration.

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Section: Discussionmentioning

confidence: 99%

Parametric Distributions for Survival and Reliability Analyses, a Review and Historical Sketch

et al. 2022

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“…• Clinical trial and sample size (Bakoyannis et al, 2021;Hu et al, 2021;Zhang & Jeong, 2021) • Computational method (de Freitas Costa et al, 2021;Huang et al, 2020;Kawakami et al, 2021;Mitra et al, 2021;Ota & Kimura, 2021) • Competing risk (Bakoyannis et al, 2021;Ha & Lee, 2021;Lipowski et al, 2021; Zhang & Jeong, 2021) • Copula (Huang et al, 2020;Lipowski et al, 2021;Ota & Kimura, 2021;Wang & Emura, 2021) • Counting or Poisson process (Dörre, 2021;Su & Lin, 2020) • Dependence modeling (Kim & Lee, 2021;Ota & Kimura, 2021; 2021) • Dynamic prediction (Kawakami et al, 2021;Mitra et al, 2021) • Ecological application (de Freitas Costa et al, 2021) • Econometric application (Dörre, 2021;Hsu et al, 2021;Lipowski et al, 2021) • Flexible parametric model (Lipowski et al, 2021;MacKenzie et al, 2021) • Frailty and random-effects models (Ha & Lee, 2021;Kawakami et al, 2021;MacKenzie et al, 2021;Wang & Emura, 2021;Zhang & Jeong, 2021) • Interval censoring (Hsu et al, 2021;Kim & Lee, 2021) • Joint frailty-copula model (Huang et al, 2020;Kawakami et al, 2021;Wang & Emura, 2021) • Left-truncation or double-truncation (Dörre, 2021;…”

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confidence: 99%