How to find out hazard ratio and confidence interval from LASSO cox regression ans plot momogram in R? I am working on a prognostic model based on time to event endpoint. The training data consists of 800 participants and test data around 400. The number of variables is 21. I was using glmnet package.
I can easily get the coefficients at minimum lambda. However, I read some articles where they have used a perturbation method to calculate the hazard ratio and 95% confidence intervals and then plot a nomogram. Can someone please help me with this. I would appreciate any help with the concept and how to apply that with R.

Your dataset is too small by a factor of >10 for split sample validation to be reliable.  It is also too small for feature selection to be reliable.  Consider data reduction (unsupervised learning), standard fitting, and resampling validation (100 repeats of 10-fold cross-validation or the bootstrap) as detailed in RMS.  Then you can use nomogram() in the R rms package.
