Results 241 to 250 of about 281,063 (279)

Comparing two crossing hazard rates by Cox proportional hazards modelling

Statistics in Medicine, 2006
AbstractMotivated by a clinical trial of zinc nasal spray for the treatment of the common cold, we consider the problem of comparing two crossing hazard rates. A comprehensive review of the existing methods for dealing with the crossing hazard rates problem is provided.
Kejian, Liu, Peihua, Qiu, Jun, Sheng
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Exclusive Hypothesis Testing for Cox’s Proportional Hazards Model

Journal of Systems Science and Complexity
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Qiang Wu, Xingwei Tong, Xiaogang Duan
openaire   +1 more source

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. Y. Lin, L. J. Wei
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Survival Analysis Cox’s Proportional Hazards Model)

2001
Abstract The San Francisco Men’s Health Study is based on a sample of 1034 single men ages 24 to 54 years. These men were recruited using a multistage prob­ ability sample and were followed from July 1984 to December 1987. Mem­ bers of the cohort were interviewed and examined every six months.
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Relating Cox's Proportional Hazard Model to the Exponential Model for Survival

Biometrical Journal, 1987
AbstractAn approximate representation is given for the partial likelihood estimate of the regression coefficient in Cox's proportional hazard model which indicates how it measures the association between survival time and covariate. The case of a single covariate is concentrated on.
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Diagnostics for Cox’s Proportional Hazards Model

2004
Although Cox’s proportional hazards model is applied so often, diagnostic methods are not well known to non-expert users. Latest results suggest that individually scaled Schoenfeld residuals, dfbetas and added variable plots should be provided for assessing the model. Most of these methods are absent from widely used packages.
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Cox Proportional Hazards Regression Model

2001
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.
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L₁Penalized Estimation in the Cox Proportional Hazards Model

Biometrical Journal, 2010
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
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Multiple Imputation for the Cox Proportional Hazards Model with Missing Covariates

Lifetime Data Analysis, 1997
We present three multiple imputation estimates for the Cox model with missing covariates. Two of the suggested estimates are asymptotically equivalent to estimates in the literature when the number of multiple imputations approaches infinity. The third estimate can be implemented using standard software that could handle time-varying covariates.
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Using fractional polynomials and restricted cubic splines to model non‐proportional hazards or time‐varying covariate effects in the Cox regression model

Statistics in Medicine, 2022
Peter Austin, Douglas S Lee
exaly