I would to ask you if it is possible to use a logistic distribution in an AFT model with brm… l can’t find a suitable function in the manual… @paul.buerkner

```
library(brms)
library(survival)
data=veteran
model <- brm(time | cens(1-status) ~ factor(trt),
data = data,
family = xxxxx () )
```

Thanks.

It is challenging for me. I have tried this, but the result does not seem to much flexsurv.

Can anybody tell me how to fix this stan code to get the logistic distribution please?

```
library(survival)
library(brms)
data= veteran
stan_code <- "
real my_logistic_lpdf(real y, real mu, real sigma) {
return -log(sigma) - 2*log1p_exp((y - mu) / sigma) - ((y - mu) / sigma);
}
real my_logistic_lcdf(real y, real mu, real sigma) {
return -log1p_exp(-(y - mu) / sigma);
}
real my_logistic_lccdf(real y, real mu, real sigma) {
return log1p_exp(-(y - mu) / sigma);
}
"
custom_stan_funs <- stanvar(scode = stan_code, block = "functions")
logistic_family <- custom_family(
"my_logistic",
dpars = c("mu", "sigma"),
links = c("identity", "log"),
lb = c(NA, 0),
type = "real"
)
custom_stan_funs <- stanvar(scode = stan_code, block = "functions")
aft_model <- brm(
formula = time | cens(1 - status) ~ trt,
data = data,
family = logistic_family,
stanvars = custom_stan_funs,
chains = 1,
iter = 1000,
seed = 42
)
library(flexsurv)
flexsurv_model <- flexsurvreg(
Surv(time, status) ~ trt,
data = data,
dist = "llogis"
)
```