One possibility might be the -somersd- package, downloadable from SSC,
together with -parmby-, part of the -parmest- package, also downloadable
from SSC. The -somersd- package calculates confidence intervals for Somers'
D and Kendall's tau-a, saving the results as estimation results. The
-parmby- command calls an estimation command (like -somersd-) and creates
an output data set with 1 observation per parameter per by-group and data
on estimates, standard errors, confidence intervals, P-values and other
>In my experience, viral loads are lognormally distributed. I would
>therefore log-transform the viral loads and use linear regression methods
>on the logs to estimate geometric means and their ratios, using the
>-eform()- option of -regress-.
Yes, this is generally true but unfortunately in my case, log-transformation
does not help. Is there a nonparametric method I can use?