Is the (non-clustered) sandwich estimator really robust to autocorrelation?
Thanks
Frank
-
Frank Harrell
Department of Biostatistics, Vanderbilt University
--
View this message in context:
http://r.789695.n4.nabble.com/robust-standard-error-of-an-estimator-tp3170257p3170363.html
Sent from t
It depends on what you mean by "robust." Robust to what?
I recommend looking at the sandwich package which gives
heteroskedasticity and autocorrelation robust variance/covariance
matrices. For instance, you could do the following to get your OLS
estimates with heteroskedasticity consistent
Hi,
I have ove the robust standard error of an estimator but I don't know how to
do this.
The code for my regression is the following:
reg<-lm(fsn~lctot)
But then what do I need to do?
--
Charlène Lisa Cosandier
[[alternative HTML version deleted]]
_
3 matches
Mail list logo