Hello, I have data with number of health conditions entered as binary variables 1 (Yes) or 0 (No), eg. asthma, clustered in sites (site_ID). I would like to use direct age standardisation using age_cat to estimate their prevalence and 95% CI, where the entire cohort is used as standard population (stand_pop). So my code would look something like:

svyset site_ID

svy: tabulate asthma, stdize(age_cat) stdweight(stand_pop_weight) ci

My understanding is that Stata uses 'standard' CI calculation assuming normal data. I would like to have CI based on Dobson method as more accurate. I know that distrate would provide such results. However, I am not sure if I can use it or adopt it for clustered data. Could you please share your thoughts on whether I should use
distrate
or just use the
svy
results or manually calculate Dobson CI? Any feedback is much appreciated.