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Weighted Cox regression for the prediction of heterogeneous patient subgroups
BMC Medical Informatics and Decision Making, 2021 Background An important task in clinical medicine is the construction of risk prediction models for specific subgroups of patients based on high-dimensional molecular measurements such as gene expression data.
Katrin Madjar, Jörg Rahnenführer
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COX PROPORTIONAL HAZARD REGRESSION SURVIVAL ANALYSIS FOR TYPE 2 DIABETES MELITUS
Barekeng, 2022 One of the most widely used methods of survival analysis is Cox proportional hazard regression. It is a semiparametric regression used to investigate the effects of a number of variables on the dependent variable based on survival time.
Umi Mahmudah +4 more
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Beyond first-order asymptotics for Cox regression [PDF]
, 2015 To go beyond standard first-order asymptotics for Cox regression, we develop parametric bootstrap and second-order methods. In general, computation of $P$-values beyond first order requires more model specification than is required for the likelihood ...
Bellio, Ruggero, Pierce, Donald A.
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Stepwise cox regression analysis in SPSS
Cancer Research, Statistics, and Treatment, 2018 This article is a beginners' guide for performing Cox regression analysis in SPSS. The article provides practical steps toward performing Cox analysis and interpreting the output of SPSS for Cox regression analysis.
Sampada Dessai, Vijai Simha, Vijay Patil
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Implementation of complex interactions in a Cox regression framework [PDF]
, 2003 The standard Cox proportional hazards model has been extended by functionally describable interaction terms. The first of which are related to neural networks by adopting the idea of transforming sums of weighted covariables by means of a logistic ...
Müller, M., Ulm, Kurt
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Box-Cox symmetric distributions and applications to nutritional data [PDF]
, 2017 We introduce the Box-Cox symmetric class of distributions, which is useful for modeling positively skewed, possibly heavy-tailed, data. The new class of distributions includes the Box-Cox t, Box-Cox Cole-Gree, Box-Cox power exponential distributions, and
Ferrari, Silvia L. P., Fumes, Giovana
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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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Censoring Balancing Functions for Undetected Probably Significant Effects in Cox Regression
International Journal of Mathematics and Mathematical Sciences, 2023 Weighted Cox regression models were proposed as an alternative to the standard Cox proportional hazards models where consistent estimators can be obtained with more relative strength compared to unweighted cases. We proposed censoring balancing functions
Ildephonse Nizeyimana +3 more
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Generating Survival Times to Simulate Cox Proportional Hazards Models [PDF]
, 2003 This paper discusses techniques to generate survival times for simulation studies regarding Cox proportional hazards models. In linear regression models, the response variable is directly connected with the considered covariates, the regression ...
Augustin, Thomas +2 more
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Weighted Cox Regression Using the R Package coxphw
Journal of Statistical Software, 2018 Cox's regression model for the analysis of survival data relies on the proportional hazards assumption. However, this assumption is often violated in practice and as a consequence the average relative risk may be under- or overestimated.
Daniela Dunkler +3 more
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