e(df_m) will tell you how many degrees of freedom your model has. If
this is less than the number of predictors (the columns of e(b) minus 1)
then something has been dropped.
David
-----Original Message-----
I am writing a program that runs through potentially tens of thousands
of regressions. During this evaluation, I sometimes end up with
collinear variables. (Not really, but very nearly collinear, and so
numerically stata ends up thinking they are.) I know that I can look
thru the e(V) matrix looking for a value of zero on the diagonal. But
doing this for every regression means another loop inside the main loop
that may run tens of thousands of times.
Does anyone know of a way to detect a dropped variable without a loop?