Matt Secrest
Matt Secrest
@ngreifer super helpful, thank you for the timely response. For me, the added information that "a PS model is fit separately within each level of the `by` variable" clears things...
We can use this thread to discuss the PEM outcome distribution.
What would be helpful is: - function name - arguments - default behavior - common errors to anticipate AFter this we can start breaking it up and writing the code.
Good function to look at would be `exp_surv_dist()`
And a good first step would be cloning the repo and getting `devtools::test()` to run.
I think this is what I got working from Manoj's original script: ``` #This R script fits a commensurate prior model using rstan. # Date: 08/04/2023 library(psborrow2) library(WeightIt) library(R2jags) example_dataframe
@gravesti this looks awesome and it runs and I agree it looks similar. The code is quite clever and I am going to need a few days for a proper...
@gravesti just tried out the approach I had in mind with mroe preprocessing in R. It gave identical results but was about 75% the sampling time. ``` data { int...
``` id ext trt cov4 cov3 cov2 cov1 status cnsr resp tstart time evnt ai 1 1 0 0 1 1 1 0 1 0 1 0 2.422641 1 1...
Bonus is also that I think it would be easier to work into the current STAN code?