Results 291 to 300 of about 402,477 (353)

Efficiency of a New Parametric Cox Proportional Hazard Model Using Monte Carlo Simulation Study

Precious O. Ibeakuzie, Sidney I. Onyeagu
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Commentary: Molecular and immunological features of TREM1 and its emergence as a prognostic indicator in glioma. [PDF]

Front Immunol
Xue J, Luo Z, Wang T, Yin Q, Chen L.
europepmc   +1 more source

A prognostic framework for predicting lung signet ring cell carcinoma via a machine learning based cox proportional hazard model

Haixin Chen, Yanyan Xu, Hao-Wen Lin, Shibiao Wan, Lianxiang Luo   +4 more
openalex   +1 more source

Goodness-of-fit tests in the Cox proportional hazards model

Communications in Statistics - Simulation and Computation, 2019
We consider a variety of tests for testing goodness-of-fit in a parametric Cox proportional hazards (PH) model and compare their performance. Aspects of the model under test include the baseline distribution and time-invariance of covariates.
M. Cockeran, S. Meintanis, J. Allison
semanticscholar   +5 more sources

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The Robust Inference for the Cox Proportional Hazards Model

Journal of the American Statistical Association, 1989
Abstract We derive the asymptotic distribution of the maximum partial likelihood estimator β for the vector of regression coefficients β under a possibly misspecified Cox proportional hazards model. As in the parametric setting, this estimator β converges to a well-defined constant vector β*.
D. Lin, L. J. Wei
semanticscholar   +3 more sources

Cox Proportional Hazards Regression Model

, 2015
The Cox proportional hazards model 132 is the most popular model for the analysis of survival data. It is a semiparametric model; it makes a parametric assumption concerning the effect of the predictors on the hazard function, but makes no assumption regarding the nature of the hazard function λ(t) itself.
F. Harrell
semanticscholar   +3 more sources

The Cox Proportional Hazards Model

, 2016
The proportional hazards (PH) or Cox model holds on E, if the hazard rate has the form $$\begin{aligned} \lambda _{x(\cdot )}(t) = r\{x(t)\} \;\lambda _0(t), \quad x(\cdot ) \in E, \end{aligned}$$ where \(\lambda _0(\cdot )\) is an unspecified baseline hazard rate function , and \(r(\cdot )\) is a positive function on E. The function \(r(\cdot )\
M. Nikulin, H. I. Wu
semanticscholar   +3 more sources

L1 Penalized Estimation in the Cox Proportional Hazards Model

Biometrical Journal, 2009
AbstractThis article presents a novel algorithm that efficiently computesL1penalized (lasso) estimates of parameters in high‐dimensional models. The lasso has the property that it simultaneously performs variable selection and shrinkage, which makes it very useful for finding interpretable prediction rules in high‐dimensional data. The new algorithm is
J. Goeman
semanticscholar   +6 more sources

Model inconsistency, illustrated by the Cox proportional hazards model.

Statistics in Medicine, 1995
AbstractWe consider problems involving the comparison of two or more treatments where we have the opportunity to adjust for relevant covariates either conditionally in a regression model or implicitly in repeated measures data, for example, in crossover trials. It is seen that for data arising from non‐Normal distributions there is the possibility that
Ian Ford, John Norrie, Susan Ahmadi
semanticscholar   +4 more sources

On using the Cox proportional hazards model with missing covariates

Biometrika, 1997
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
M. Paik, W. Tsai
semanticscholar   +3 more sources