|From||Scott Cunningham <email@example.com>|
|Subject||Re: st: A question about modelling heterogenous variances|
|Date||Fri, 21 Oct 2005 12:22:16 -0400|
Tim, I apologize. I responded, but this paragraph was cut off becuase of how my mail server deliivers the mail to me. I didn't see you'd already considerd -robust-.
One of the great features of Stata is its robust option in many estimation
commands. Theoretically in normal linear regression, it replaces the
variance matrix of our error (e) with an empirical one based on the
residuals. I foresee that one solution to my problem would be to create a
variance matrix that is half way between the OLS and this empirical one,
that is one that has its residuals averaged within each group (site). One
problem with the robust option is that often if my subgroup size is too
small, it gives rubbish estimates of Standard error. I wonder if this
could be a solution to this too. Has anyone done methodological
investigation into this technique?