[QUESTION] `posterior_traj()` for `stan_mvmer`

Summary:

Is it possible to make dynamic prediction for a multivariate mixed model without the survival component?

Description:

Hi, thanks for developing rstanarm and stan! I am interested in modelling two longitudinal continuous outcomes (without any survival component). I can fit the model I am interested with using stan_mvmer (see steps below). Now I am interested in obtaining dynamic predictions, as it can be done for a stan_jm object using the post_traj function. I think (!) that it should be possible to obtain longitudinal dynamic predictions for a multivariate mixed model, but at the moment post_traj only accepts stan_jm objects. Would it be possible to extend post_traj?

Reproducible Steps:

fit <- stan_mvmer(
  formula = list(
    Y1 ~ TIME + BL1 + (TIME | PATNUM),
    Y1 ~ TIME + BL2  + (TIME | PATNUM)
  ),
  data = train_df, 
  # this next line is only to keep the example small in size!
  chains = 2, cores = 2, seed = 12345, iter = 1000
)

RStanARM Version:

2.21.3

R Version:

4.2.0

Operating System:

x86_64-pc-linux-gnu (64-bit)

Thanks for the help, best wishes
Francesco

Start with the post_traj entry point and the stan_mvmer object produced by the reproducible example. Determine how dynamic predictions should be represented for multivariate longitudinal outcomes without a survival component, then validate the proposed behavior against the example model and existing stan_jm usage.