**110**wrote:

I am learning survival analysis in R, especially the Cox proportional hazard model. I read a paper talking about using 80% of the sample as training set and 20% of sample as test set.

As quoted "*On the training set, we first performed a pre-selection step to keep the top significant features correlated with overall survival (univariate Cox model, likelihood ratio test, P < 0.05). ... We used two computational methods to train the models: (i) Cox: the Cox proportional hazards model with LASSO for feature selection ... We then applied the models thereby obtained to the test set for prediction, and calculated the C-index using the R package survcomp.*"

I do not know how they actually did to apply the models from Cox model to the test set. I mean, for the training set, I can simply perform a coxph function. But the returned results are "coef,exp(coef),se(coef)),z,p" and likelood ratio test p-value. How can I treat this as a model and use it on the 20% test set data?

**0**• written 5.9 years ago by hdy •

**110**

could you give the reference, please

5.4kpaper name "Assessing the clinical utility of cancer genomic and proteomic data across tumor types" is on nature biotechnology. Thanks!

110