Hi:
I think I found an error in plot.lm with the option which=5, of course I
can be wrong , as usually happen, but I had work on it for a while and show it
to some other people that work with R, and so far I don't see what I can be
interpreting wrong. I also worked over the plot.lm's code and change some lines
to get what I call "the right plot", if any body is interested I can send the
modified code to see what is the problem I think I found and what could be a
solution.
I´m working with R 2.4.0 on windows XP, and here is a reproducible example,
(this example is just to show the problems in the plot and it doesn't make any
sense the way I analyzed).
set.seed(3)
datos <-data.frame(fac.A=rep(c("bla","Ur2","pel","arb"),each=3),
y= c(rnorm(3,sd=0.5),rnorm(9,sd=2)))
model1 <- lm(y~fac.A,data=datos)
plot(model1,which=5) # plot1
# this plot1 show that level "arb" has less dispersion than the other levels,
# But if I do the plot by myself, look:
hii <- lm.influence(model1, do.coef = FALSE)$hat
s1 <- sqrt(deviance(model1)/df.residual(model1))
rs <- residuals(model1)/(s1 * sqrt(1 - hii))
plot(rs~datos$fac.A) # plot2
# this plot2 show me that level "bla" is less variable.
# also per and Url have some problems but this give you the idea of what I
think Is wrong.
What I have found in the code, is that for this option (which=5), the labels
of the x axis are ordered in a way that the predicted value for the levels are
increasing, but when it actually do the plot it doesn't keep that order.
Thanks for your time (and sorry for my English) .
Gabriela
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