I have a Cox proportional hazards model set up using the following code in R that predicts mortality. Covariates A, B and C are added simply to avoid confounding (i.e. age, sex, race) but we are re...

Currently my forest plots for subgroup analysis (not for meta-analysis) in R are like the following... library("dplyr") library(ggplot2) library(survminer) library(survival) library(fores...

I'm using R's coxph function to fit a survival regression model, and I'm trying to model time dependent covariates (see this vignette). When fitting the model, I get the following error: Error in ...

Are there any packages in Python for survival analysis? Specifically, I am interested in performing a Cox regression? I know this example but it's in R. Could we just interface Python with R (using...

Running a survival analysis, assume the p-value regarding a variable is statistically significant - let's say with a positive association with the outcome. However, according to the Schoenfeld resi...

In R, what is the best way to incorporate the interaction term between a covariate and time, when the proportionality test (with coxph) shows that the proportionality assumption in the Cox model is...

I use a best subset selection package to determine the best independent variables from which to build my model (I do have a specific reason for doing this instead of using the best subset object di...

when i run coxph(Surv(Time, Status)~Class, data = df) on data set like below it always sets the reference group by alphabetical order, in this case MutantA would be the reference group. Is there a ...

there is quite a lot of information (internet and textbooks) on how to do survival analysis in R with the survival package. But I don't find any information on how to do this when you have left cen...

I have a dataset with survival data and a few missing covariates. I've successfully applied the mice-package to imputate m-numbers of datasets using the mice() function, created an imputationList o...

I have a modeled a problem using Cox's regression and now want to predict the estimated survival time for an individual. The model has a list of covariates on which the survival time depends. This ...

I am trying to find a way to model Survival Models for Recurrent Events in Python, especially the Counting process approach using CoxPH. In Counting Process Approach, it is expecting start-time and...

I am puzzled at a behaviour of a function that I am trying to write. My example comes from the survival package but I think that the question is more general than that. Basically, the following cod...

I want to select a Cox model with the forward procedure from a data.frame with no NA. Here is some sample data: test <- data.frame( x_1 = runif(100,0,1), x_2 = runif(100,0,5), x_3 = runif(10...

I want to plot the estimated hazard ratio as a function of time in the case of a coxph model with a time-dependent coefficient that is based on a spline term. I created the time-dependent coefficie...

I have a following model: coxph(Surv(fulength, mortality == 1) ~ pspline(predictor)) where is fulength is a duration of follow-up (including mortality), predictor is a predictor of mortality. T...

I have a coxph model with 5 time-dependent and 2 time-independent variables. I want to test the proportional hazards assumption and besides martingale and deviance residuals, using cox.zph. My ques...

I'm having some trouble using coxph(). I've two categorical variables:"tecnologia" and "pais", and I want to evaluate the possible interaction effect of "pais" on "tecnologia"."tecnologia" is a var...

I'm having some trouble using coxph(). I've two categorical variables: Sex and Probable Cause, that I want to use as predictor variables. Sex is just the typical male/female but Probable Cause has ...

I wan't to export the output from a cox regression to a table that I then can put into my article. I guess the best way to go about it is with xtable: library(survival) data(pbc) fit.pbc <- cox...