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A Weibull-Frechet Proportional Hazard Model with Application to Tuberculosis Data

Abdulfatai Lawal, Tasi apos u Musa, Aliyu Yakubu   +2 more
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Prediction models and risk scores in different types of heart failure: a review. [PDF]

Front Med (Lausanne)
Wei Y, Liu S, Mu Y, Liang X, Chen Z, Liu Y, Dong G.   +6 more
europepmc   +1 more source

Cox proportional hazards model evaluating the impact of IC on all-cause mortality.

Kelly M. Pennington (18414686), Herb Heien (22103798), Hemang Yadav (22103801), Xiaoxi Yao (6176327), Bradley White (4476466), Steve G. Peters (22103804), Patricio Escalante (6372638), Che Ngufor (3880168), Raymund R. Razonable (12730956), Cassie C. Kennedy (13719787)   +9 more
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Competing risk analysis of prognosis in patients with uveal melanoma. [PDF]

Discov Oncol
Huang R, Chen J, Lyu J, Zhou Q, Lin L.
europepmc   +1 more source

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Proportional hazards models

2011
This chapter discusses the most widely used regression models in competing risks. Following an introduction in Section 5.1, Section 5.2 discusses proportional cause-specific hazards models, and Section 5.3 discusses the proportional subdistribution hazards model. The cause-specific hazards are as defined in Chapter 3.
Jan Beyersmann, Martin Schumacher, Arthur Allignol   +2 more
openaire   +2 more sources

Analysis of noisy survival data with graphical proportional hazards measurement error models

Biometrics, 2020
In survival data analysis, the Cox proportional hazards (PH) model is perhaps the most widely used model to feature the dependence of survival times on covariates. While many inference methods have been developed under such a model or its variants, those
Li‐Pang Chen, G. Yi, Department of Statistical, A. Sciences   +3 more
semanticscholar   +1 more source

Misspecified Proportional Hazard Models

Biometrika, 1986
Let \((N_ i(t)\), \(t\geq 0\), \(i=1,...,n)\) be a counting process in which \(N_ i(t)\) records the number of failures in [0,t] for i-th item, and let \(Y_ i(t)\lambda_ 0(t) \exp (\beta Z_ i)\) \((i=1,...,n)\) be a random intensity process (for \(N_ i)\).
Struthers, C. A., Kalbfleisch, J. D.
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Reliability assessment for systems suffering common cause failure based on Bayesian networks and proportional hazards model

Quality and Reliability Engineering International, 2020
The Bayesian network (BN) is an efficient tool for probabilistic modeling and causal inference, and it has gained considerable attentions in the field of reliability assessment.
Yanfeng Li, Yang Liu, Tudi Huang, Hongzhong Huang, J. Mi   +4 more
semanticscholar   +1 more source

Tree-Structured Proportional Hazards Regression Modeling

Biometrics, 1994
A method for fitting piecewise proportional hazards models to censored survival data is described. Stratification is performed recursively, using a combination of statistical tests and residual analysis. The bootstrap is employed to keep the probability of a Type I error (the error of discovering two or more strata when there is only one) of the method
Ahn, Hongshik, Loh, Wei-Yin
openaire   +3 more sources