[HTML][HTML] Time-varying covariates and coefficients in Cox regression models
Time-varying covariance occurs when a covariate changes over time during the follow-up
period. Such variable can be analyzed with the Cox regression model to estimate its effect …
period. Such variable can be analyzed with the Cox regression model to estimate its effect …
Understanding the Cox regression models with time-change covariates
M Zhou - The American Statistician, 2001 - Taylor & Francis
The Cox regression model is a cornerstone of modern survival analysis and is widely used
in many other fields as well. But the Cox models with time-change covariates are not easy to …
in many other fields as well. But the Cox models with time-change covariates are not easy to …
Generating survival times to simulate Cox proportional hazards models with time‐varying covariates
PC Austin - Statistics in medicine, 2012 - Wiley Online Library
Simulations and Monte Carlo methods serve an important role in modern statistical
research. They allow for an examination of the performance of statistical procedures in …
research. They allow for an examination of the performance of statistical procedures in …
Time-dependent covariates in the Cox proportional-hazards regression model
LD Fisher, DY Lin - Annual review of public health, 1999 - annualreviews.org
▪ Abstract The Cox proportional-hazards regression model has achieved widespread use in
the analysis of time-to-event data with censoring and covariates. The covariates may change …
the analysis of time-to-event data with censoring and covariates. The covariates may change …
On the Cox model with time-varying regression coefficients
In the analysis of censored failure time observations, the standard Cox proportional hazards
model assumes that the regression coefficients are time invariant. Often, these parameters …
model assumes that the regression coefficients are time invariant. Often, these parameters …
Weighted Cox regression using the R package coxphw
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 …
assumption. However, this assumption is often violated in practice and as a consequence …
A comparison of time dependent Cox regression, pooled logistic regression and cross sectional pooling with simulations and an application to the Framingham Heart …
JS Ngwa, HJ Cabral, DM Cheng, MJ Pencina… - BMC medical research …, 2016 - Springer
Background Typical survival studies follow individuals to an event and measure explanatory
variables for that event, sometimes repeatedly over the course of follow up. The Cox …
variables for that event, sometimes repeatedly over the course of follow up. The Cox …
[PDF][PDF] Cox proportional-hazards regression for survival data
J Fox, S Weisberg - An R and S-PLUS companion to applied …, 2002 - gilbertresearch.org
Survival analysis examines and models the time it takes for events to occur, termed survival
time. The Cox proportional-hazards regression model is the most common tool for studying …
time. The Cox proportional-hazards regression model is the most common tool for studying …
Tutorial: survival estimation for Cox regression models with time-varying coefficients using SAS and R
L Thomas, EM Reyes - Journal of Statistical Software, 2014 - jstatsoft.org
Survival estimates are an essential compliment to multivariable regression models for time-
to-event data, both for prediction and illustration of covariate effects. They are easily …
to-event data, both for prediction and illustration of covariate effects. They are easily …
Efficiency of the logistic regression and Cox proportional hazards models in longitudinal studies
I Annesi, T Moreau, J Lellouch - Statistics in medicine, 1989 - Wiley Online Library
Both logistic regression and Cox proportional hazards models are used widely in
longitudinal epidemiologic studies for analysing the relationship between several risk factors …
longitudinal epidemiologic studies for analysing the relationship between several risk factors …