I want to use glmnet cox regression approach to predict survival from methylation data for cancer patients. But I couldn't find any proper reference except this one https://cran.r-project.org/web/packages/glmnet/vignettes/Coxnet.pdf, discussing its prediction values.
I am looking for answers to my basic questions.
I trained the model using real patient data, where I provided both "overall survival" as well as "vital status of the patient" from the training set. After training, When I used test data for prediction, It is giving some values with negative sign?
I assume these are number of days for which patient will survive after diagnosis, but I couldn't understant the meaning of minus sign with these values. Does these minus sign denote status of the patients.
Please correct me if I am getting it wrong.
I am new with data science and also with R. Any help and suggestions are welcome.
Thanks in advance
Best Answer
A Cox model is an ingenious way to estimate effects on a response with censoring. However, it it not designed to predict times or status (although it is possible by making a lot of assumptions). Instead, it would predict the hazard/risk (if type = "response") which is useful e.g. to calculate a hazard ratio between two predictions/subjects. If you don't set "type" you will get the value of the linear predictor.
My suggestion is to have a minimal understanding of the used methods. In this case of Cox regression.