I don't know lme models very well, but if you have standard errors for your
values, this shouldn't be too hard (as a last resort) using polygon()

For example

x = 1:10
y = x^2
y.Err = 2*x
y.Up = y + y.Err; y.Dn =y-y.Err

# This graph is actually quite ugly so don't copy the formatting....
plot(x,y,type="n")
polygon(c(x,rev(x)),c(y.Up,rev(y.Dn)),col="grey",border="red")
# Use the rev commands so the border moves logically around the shaded area
lines(x,y,type="b",lwd=3) # put the means back on top of the polygon

Still, this is a little brute force and I'd imagine that someone else will
shortly let you know how R can already do automatically.

Michael Weylandt

On Mon, Aug 8, 2011 at 1:07 PM, bjmjarrett <bjmjarrett@gmail.com> wrote:

> Hi all,
>
> I’m trying to plot confidence intervals for the fitted values I get with my
> lme model in R.
>
> Is there any way I can plot this in the form of a shaded band, like the
> output of geom_smooth() in ggplot2 package. ggplot2 seems to use only lm,
> glm, gam, loess and rlm as smoothing methods.
>
> Any advice on the functions I should use to accomplish this will be very
> helpful.
>
> Thank you very much.
>
> Ben
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/confidence-interval-as-shaded-band-lme-tp3727645p3727645.html
> Sent from the R help mailing list archive at Nabble.com.
>
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