Plotting GEE confidence bands using "predict"

Hello Fellow R
Users,I have
spent the last week trying to find a work around to this problem and I can't
seem to solve it. I simply want to plot my GEE model result with 95% confidence
bands.


I am using the geepack package to run a basic GEE model involving
nestling weights, to a Gaussian distribution, with "exchangeable" error
structure. I am examining how nestling weight varies as a function of distance
from a plot boundary.



The response variable (WEIGHT) and the explanatory
variable (DISTANCE) are both continuous. The clustering factor (MOTHER) is
entered into my model to account for similarity of nestlings from the same nest
produced by a given mother.


My simplified code is
as follows:


summary(model1<-geeglm(WEIGHT~DISTANCE,
id=MOTHER,data=df,corstr="exchangeable")))
#I've included part of the
model output
here



<Coefficients:
<
? ? ? ? ? ? ? ? ?Estimate Std.err
?Wald ? ? ? ? Pr(>|W|)

<(Intercept) ? ? 15.8702 ?0.4416
1291.8 ?< 2e-16 ***
<Initiationdate ?-0.0664
?0.0157 ? 17.9 ? ? ? ? ?2.4e-05
***
<
<Estimated Scale
Parameters:
<
< ? ? ? ? ? ?Estimate
Std.err
<(Intercept) ? ? 5.78
?2.46






plot(df$DISTANCE,df$WEIGHT)


abline(model1)


x<-seq(min(df$DISTANCE),max(df$DISTANCE),l=1000)


y<-predict(model1,data.frame(DISTANCE=x))


Everything is fine up until this last line of code, when I get the following
error message:



"Warning message:
In predict.lm(object, newdata, se.fit, scale = 1, type = ifelse(type == ?:
?calling predict.lm(<fake-lm-object>) ..."



This isn't a geepack problem because I get the same error message using the gee
package as well. The above simplified code is how I usually create and plot 95%
CI bands for a linear model, followed by:


matlines(x,y)


I have read through the package PDFs and searched the web and archives of
various listservs without success. Any help would be most appreciative. Seems
like there should be a simple work-around. Thank you,
Jason






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