On Jun 23, 2009, at 3:08 AM, Chris Friedl wrote:
I appreciate that you are trying to help me but I don't fully
understand your
point.
The point is that in very few applications can one legitimately
"exclude" an intercept. In this situation (stepwise regression) I am
able to think of a way to make the intercept just another covariate,
but I see theoretic objects with that approach. Of course there are
problems with stepwise regression as well.
At one point I did say "... the intercept is not significantly
different from zero". I admit I also said "dropping the intercept
term"
which in my loose application of terminology means force the
intercept to a
value of zero. So yes the intercept exists and it has a value but
that value
is not significantly different from zero. This does not make the
intercept
non-significant or exclude an intercept in any way. If that was your
point
then I stand corrected for my loose use of terminology. If not, then
perhaps
you can expand a little more.
Perhaps the following will explain what I'm after. Fitting y ~ x1+x2
for
dataframe d1 gives the following:
summary(lm(y~x1+x2, data=d1))
OK, this is on your head. Make sure you know how not to burn yourself
with this:
> model <- y ~ x1*x2 + one -1
> data2$one <- 1
> by(data2, data2$grp, function(x) step(lm(model, data=x)))
Lets the intercept just be another variable.
<snip>
For my real application theory would suggest the intercept is zero
for each
of the thousands of groups in my dataset. Of course I can fit y ~
x1+x2 and
where the summary info suggests the intercept is not significantly
different
from zero, refit y ~ -1+x1+x2. I just wondered whether step or some
other
function could do that for me in one R expression.
Thanks again.
David Winsemius wrote:
I think you should explain (to yourself primarily) what it means to
have a non-significant intercept. If you can justify on a theoretic
basis the exclusion of an intercept, then you may get more
assistance.
However, if you are just naively questing after some mythical concept
of "significance", people may be less motivated to solve what most
would consider to be an "insignificant" question.
--
DW
David Winsemius, MD
Heritage Laboratories
West Hartford, CT
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