STORE equivalent in PROC MCMC

lsandell — Sun, 05 Feb 2023 19:20:17 GMT

I am fitting a logistic regression in PROC MCMC and need to calculate the 95% HPD Credible Interval on the Odds Ratio (exponentiated) scale for each chain before taking the average across chains. Rather than taking the average posterior mean(s) and interval values and then exponentiating, I need to exponentiate means and interval values and then take the average. The BAYES statement has the STORE option so that posterior samples and 95% CrI can be determined. Note: I need to use PROC MCMC, so any solutions with GENMOD aren't desired.

How could I accomplish this, either through an existing statement or through a manual calculation? Thanks!

proc mcmc data=data.XX 
	plots=all
	nbi=1000 
	nmc=9000 
    seed=123 
	dic 
	plots(smooth)=all 
	statistics=all
	outpost=post1;
  	parms (beta0 B_tx) 0;
	prior beta0 ~ normal(0,var=1);
	prior B_tx ~ normal(0,var=1);
	p = logistic(beta0 + B_tx*tx);
	model outcome ~ binary(p);
run;

Re: STORE equivalent in PROC MCMC

SAS_Rob — Mon, 06 Feb 2023 17:45:17 GMT

You could do something similar to this example in the documentation to compute posteriors for the odds ratios.

SAS Help Center: Missing at Random Analysis

topic Re: STORE equivalent in PROC MCMC in Statistical Procedures

STORE equivalent in PROC MCMC

Re: STORE equivalent in PROC MCMC