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Testing and interpreting assumptions of COX regression analysis
Cancer Research, Statistics, and Treatment, 2019 The COX regression analysis is like any statistical test that is based on multiple assumptions. This is a guide for how to test the assumptions and how to interpret the results.
Sampada Dessai, Vijay Patil
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FAKTOR-FAKTOR YANG MEMPENGARUHI DAYA TAHAN MAHASISWA TEKNIK SIPIL UIB DALAM MEMPERTAHANKAN STUDINYA
E-Jurnal Matematika, 2021 Linear regression model cannot be used to analyze the relationship between survival time and independent variables, it is because the linear regression model is not able to handle censored data.
MAHFUZ HUDORI
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A mixed model approach for structured hazard regression [PDF]
, 2004 The classical Cox proportional hazards model is a benchmark approach to analyze continuous survival times in the presence of covariate information. In a number of applications, there is a need to relax one or more of its inherent assumptions, such as ...
Fahrmeir, Ludwig, Kneib, Thomas
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An exact corrected log-likelihood function for Cox's proportional hazards model under measurement error and some extensions [PDF]
, 2002 This paper studies Cox`s proportional hazards model under covariate measurement error. Nakamura`s (1990) methodology of corrected log-likelihood will be applied to the so called Breslow likelihood, which is, in the absence of measurement error ...
Augustin, Thomas
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Nonparametric Bayesian hazard rate models based on penalized splines [PDF]
, 2003 Extensions of the traditional Cox proportional hazard model, concerning the following features are often desirable in applications: Simultaneous nonparametric estimation of baseline hazard and usual fixed covariate effects, modelling and detection of ...
Fahrmeir, Ludwig, Hennerfeind, Andrea
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E-Jurnal Matematika, 2013 Survival analysis is a statistical method that accommodates the collection of censored data. One of popular method in survival analysis is the Cox Proportional Hazard Regression.
I GEDE ARI SUDANA +2 more
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Predictive maintenance using cox proportional hazard deep learning
Advanced Engineering Informatics, 2020 Predictive maintenance (PdM) has become prevalent in the industry in order to reduce maintenance cost and to achieve sustainable operational management.
C. Chen +6 more
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Computational and Structural Biotechnology Journal, 2022 Background: Cox proportional hazard regression (CPH) model relies on the proportional hazard (PH) assumption: the hazard of variables is independent of time. CPH has been widely used to identify prognostic markers of the transcriptome.
Zihang Zeng +7 more
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Geoadditive hazard regression for interval censored survival times [PDF]
, 2005 The Cox proportional hazards model is the most commonly used method when analyzing the impact of covariates on continuous survival times. In its classical form, the Cox model was introduced in the setting of right-censored observations.
Kneib, Thomas
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Cox regression survival analysis with compositional covariates: application to modelling mortality risk from 24-h physical activity patterns [PDF]
, 2020 Survival analysis is commonly conducted in medical and public health research to assess the association of an exposure or intervention with a hard end outcome such as mortality. The Cox (proportional hazards) regression model is probably the most popular
Chastin, S.F.M. +4 more
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