Hello @paul.buerkner , I would like to know how to obtain the cumulative baseline hazard for a Cox model in brms, to estimate the survival probability at each time point. In the R survival package this is done with the basehaz function. How is it done after brms?

brms has currently no exported function that computes the cumulative baseline hazard, unfortunately.

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OK, then, would you recommend a kludge like this?

```
fit <- brm(time | cens(1 - event) ~ 1 + arm,
data = data, family = brmsfamily("cox"))
```

… where arm is a binary variable (0,1).

After that, I estimate the survival rate at the time point of interest by Kaplan-Meier (e.g. survival at 5 years = 0.50) for arm = 0.

I apply the equation of the brms Cox model on the draws and obtain the difference in survival rates:

`draws<-data.frame(fit %>% gather_draws(b_arm)) %>% mutate(Sexp= 0.50^exp(draws$.value)) %>% mutate(Sdiff= Sexp- 0.50)`

Finally, I use these model’s draws to estimate posterior probabilities on the difference. For example:

```
F<- function (value) ecdf(draws$Sdiff)(value)
F(0)
F(-0.03)
```

Etc…

Does it seems to be sound?

How about stan_surv()?