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Bias of Maximum-Likelihood estimates in logistic and Cox regression models: A comparative simulation study [PDF]
, 2003 Parameter estimates of logistic and Cox regression models are biased for finite samples. In a simulation study we investigated for both models the behaviour of the bias in relation to sample size and further parameters.
Lenz-Tönjes, Rebecca +7 more
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Survival Analysis II: Cox Regression [PDF]
Nephron Clinical Practice, 2011 In contrast to the Kaplan-Meier method, Cox proportional hazards regression can provide an effect estimate by quantifying the difference in survival between patient groups and can adjust for confounding effects of other variables. The purpose of this article is to explain the basic concepts of the Cox regression method, and to provide some guidance ...
Stel, V.S. +4 more
openaire +4 more sources
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
doaj +1 more source
Российский кардиологический журнал, 2021 The absence of consensus regarding the reference values of right ventricular free wall longitudinal strain (RVFWLS) and its predictive value prompted us to conduct a systematic review and meta-analysis of publications on the predictive role of this ...
E. Z. Golukhova +6 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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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
doaj +1 more source
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, Martina, Müller, M., Ulm, Kurt
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Using Wavelet Shrinkage in the Cox Proportional Hazards Regression model (simulation study) [PDF]
المجلة العراقية للعلوم الاحصائية, 2022 The proposed method in this paper dealt with the problem of data contamination in the Cox Proportional Hazards Regression model (CPHRM) by using Wavelet Shrinkage to de-noise data, calculating the discrete wavelet transformation coefficients for wavelets
taha ali, Jwana Rostam Qadir
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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 ...
Blettner, Maria +3 more
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Combining heterogeneous subgroups with graph-structured variable selection priors for Cox regression
BMC Bioinformatics, 2021 Background Important objectives in cancer research are the prediction of a patient’s risk based on molecular measurements such as gene expression data and the identification of new prognostic biomarkers (e.g. genes).
Katrin Madjar +3 more
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