On Sep 13, 2011, at 11:56 AM, David Winsemius wrote:
On Sep 13, 2011, at 11:44 AM, David Winsemius wrote:
On Sep 13, 2011, at 9:43 AM, RCulloch wrote:
Dear John,
Thank you for that, and for explaining why the abline() command
wont/dosen't
work. The approach is based on reviewers comments that I am a tad
sceptical
about myself but yet curious enough to test their
suggestion......I don't
think it is very straightforward to explain; however, it involves
using the
residuals of the lm() and plotting them against a covariate to
assess
whether or not the deviation from the 1:1 relationship is in someway
influenced by the other covariate.
Is the reviewer perhaps saying this will display departures from a
"linear" or "straight-line" relationship? If so, then I agree entirely
with the reviewer.
I hope that shines a small amount of
light on this rather unorthodox approach?!
Plotting the residuals against a covariate is a standard way to
assess the assumption that the residuals are distributed normally
around each continuous regressor
I've been corrected offline on this point by another "reviewer", one
who I consider highly reputable. The regression assumption is that
residuals are normal around the "true" relationship, but since we
only have the predicted relationship, the usual second-best is to look
at:
plot( fitted(fit), resid(fit))
Furthermore normality is generally not important. (I did know that.)
and have no non-linear relationship around each continuous regressor
That point is still valid.
Forgot to include homoschedasticity:
...and have a reasonably constant standard deviation across the
range of the regressor...
Also should be plotting against fitted() rather than regressors. _My_
external reviewer is of the opinion : "constant variance -- which,
again, usually is of no importance for estimation anyway unless the
heteroscedacity is huge-", but I think opinions about what constitutes
"huge" or "too much" variance may vary.
. It is not to assess a "1:1 relationship", whatever that is. I
think we would need to see a complete quotation of the reviewer's
comments before deciding who is confused in this interchange.
--
David Winsemius, MD
West Hartford, CT
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