On Mon, 20 Dec 2010, JoonGi wrote:
First of all, thanks for your guide!
Let me be more specific, here.
Using
data(Housing) from Ecdat library
I ran a regression
raw.model<-lprice~llot+lbed+lbath+lsto+factor(driveway)+factor(recroom)+factor(fullbase)+factor(gashw)+factor(airco)+factor(prefarea)+factor(garagepl)
coeftest(lm(raw.model))
and I got heteroskedasticity in significant level 5% such as below.
bptest(lm(raw.model))
So, I corrected like this.
sqrt(diag(hccm(lm(raw.model),type="hc1")))
This gave me the corrected std.errors.
From this moment, I want to test whether my parameters are individually and
jointly significant since the new std.error will change
coeftest(lm(raw.model))'s t, p and F value.
Then, How can I get these new t, p, F? Is there any R command for this?
You can team up coeftest() with other "vcov" functions, such as hccm()
from "car" or vcovHC() from the "sandwich" package. Actually, there is an
example on ?coeftest for the latter.
Also, there are various worked examples in
vignette("sandwich", package = "sandwich")
Best,
Z
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