I would like to be able to construct hazard rates (or unconditional death prob) for many subjects from a given survfit.

This will involve adjusting the ( n.event/n.risk)
with (coxph object )$linear.predictors
I must be having another silly day as I cannot reproduce the linear predictor:

fit <- coxph(Surv(futime, fustat) ~ age, data = ovarian)
fit$linear.predictors[1]
[1] 2.612756

coef(fit)*model.matrix(fit)[1,1]
     age
11.69021

The above is based on the help listing for coxph.object
coefficients: the coefficients of the linear predictor, which multiply
          the columns of the model matrix.  If the model is
          over-determined there will be missing values in the vector
          corresponding to the redundant columns in the model matrix.

Also, please comment whether n.event/n.risk gives the baseline hazard exp(alpha) ?

Please, help. Thanks a lot.

Stephen B


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