A previous post had discussed differences between dimension reduction through principal components and factor analysis on the one hand and inverse covariance weighting (ICW) on the other: [link].
I had made R code available that allows one to play around with these comparisons: [.R].
Here is a link to a Stata .ado for ICW index construction: [.ado]. The .ado file itself contains instructions on using the function “make_index_gr”, which generates an ICW index that can include weights and can be set to standardize with respect to any subset of the data (e.g., against the control group).
Please give them a try and if you find any bugs, please let me know. Also, if anyone wants to do a more professional job with the coding, and even integrate them into broader packages, please be my guest.