Joint longitudinal + time-to-event modelling in Julia?

Hi everyone,

I am new to Julia, and curious if somebody did any work on joint modelling of longitudinal and time-to-event data already and can share any code examples as starting points for me?



I’m not familiar with any Julia implementations of joint modeling. If you’re familiar with Stan, there’s the implementation done for rstanarm here:

with supporting documentation on the method here:

I think this could be readily translated to something like Turing.jl if you want a similarly Bayesian approach, but a direct translation of the Stan code would not be appealing to me (nothing against the authors of that code, just a reflection of the differences between the domain-specific language of Stan and the expressiveness of Julia).

Thanks @awasserman - yeah we do also have our own stan implementations already of these models, but would like to explore Julia now and see if that improves the code readability / maintenance outlook while maintaining or improving speed etc. I guess we get started from Tutorials - unless somebody has some code already :slight_smile:

Then converting them to Turing might not be that difficult if you already know the math and how your model functions, you’ll only have to learn how Turing works :slight_smile: