Posterior predictions of time to event using `stan_jm` and `rstanarm`

Modeling
1

Hello,
I asked part of this question in an old thread, but I’m guessing that it is not as simple as I had hoped (or that the thread is a bit stale). I have a joint longitudinal survival model (fit using the B-splines baseline hazard). I’d like to be able to generate posterior predictions of the time to event (rather than the survival probability), but am having trouble figuring out how to do that. Using posterior_predict returns a matrix with the number of observations equal to the number of observations in the longitudinal model (i.e., the number of individuals * the number of observations, not the number of individuals). When I access the “Event” portion of the model, I can see a variety of quantities, but it’s unclear whether the values of the association parameter are actually incorporated into those values. So my question is essentially, is there a way to generate posterior draws of the time-to-event for each individual in the sample. Or a way to calculate that based on the posterior estimates of the survival probability? Not sure if @bgoodri (who was involved in the other thread) or @sambrilleman have thoughts on this?

2

In case it helps, here is the rstanarm call. The particulars of the data are not important, but it’s possible that some combination of my syntax prevents estimating the time to event?

mod7 <- stan_jm(formulaLong = log1p(runarea) ~ time * hfra + I(time^2) + (time * hfra | ID),
                dataLong = fire_long_sort,
                family = gaussian,
                formulaEvent = survival::Surv(plan_time, cwpp_pres) ~ bonding + I(bonding^2) + bridging + linking + I(linking^2), 
                dataEvent = cwpp_surv_sort,
                id_var = "ID",
                time_var = "time",
                assoc = c("etavalue", "etaslope"),
                adapt_delta = 0.97,
                basehaz_ops = list(df = 8),
                max_treedepth = 20,
                chains = 6, cores = 6, refresh = 500, seed = 12345)