I have a survival model calculated like this:

mv.cox <- coxph(Surv(as.numeric(Time), as.numeric(Status))  ~Sex, data = as.data.frame((df))) 

I am looking for a way to calculate a bootstrap for this model/data that should include the Hazard ration, CI and p-value.

I tried using the the following, but it does not give the Hazard or p-value:

library(coxed)

coxed(model, method="npsf", bootstrap = TRUE, B=1000)

I also tried the rms package:

require(rms)

mv.cph <- cph(Surv(as.numeric(Time), as.numeric(Status))  ~df$miRNA,x=T,y = T, data = as.data.frame((df))) 
bootcov(mv.cph)

But not sure what the output mean:

bootcov(mv.cph)
Cox Proportional Hazards Model

 cph(formula = Surv(as.numeric(Time), as.numeric(Status)) ~ df$miRNA, 
     data = as.data.frame((df)), x = T, y = T)

                        Model Tests    Discrimination    
                                              Indexes    
 Obs        86    LR chi2     12.44    R2       0.137    
 Events     45    d.f.            1    Dxy      0.316    
 Center 0.2771    Pr(> chi2) 0.0004    g        0.581    
                  Score chi2  14.41    gr       1.788    
                  Pr(> chi2) 0.0001                      

    Coef   S.E.   Wald Z Pr(>|Z|)
 df 0.2122 0.0606 3.50   0.0005