I have done a LASSO / Cox model run for a large dataset of 10K observations which has 1200 Variables.
fit <- glmnet( x, Surv(time, status), alpha=1, family='cox') cv.fit <- cv.glmnet(x, Surv(time, status), alpha=1, family='cox')
After CV the model selected 56 variables which have non-zero coefficients, some of the coefficients have negative values and some have positive. I would like to know whether we say something about their significance with respect to the coefficient values of the variables?
What we can say about coefficients with negative value and coefficient with positive value?
Some Variables and its Coefficients Values CSI_SUPPORT -2.51E-19 Power.Glass.Moonroof 0.046261522 FLOOR_PLAN_SUPPORT -0.005169085 R.Design.Nubuck.Off.Black 0.254841459 TOTAL_AMOUNT -6.19E-05 K36100 -0.062819229 K36100 -0.237663697 Textile.Off.Black.seats 0.159802697 Design.Leather.Black -0.401298769 MARKETING_SUPPORT -0.000182012