Thank you Shige,I got the Zelig package to work for me. For anyone who cares, here's the code: library(Zelig)order(df$WEIGHT)z.out<- zelig(WEIGHT~DISTANCE, model = "normal.gee",id = "MOTHER", data = df,corstr = "exchangeable")summary(z.out)date.range<-0:51 # sequence of values over the range of DISTANCEx.high <- setx(z.out,DISTANCE=date.range)x.low <- setx(z.out,DISTANCE=date.range)s.out <- sim(z.out, x = x.low, x1 = x.high)summary(s.out)plot.ci(s.out,col="RED")abline(z.out) The "plot.ci" function produces a plot without confidence bands, per se. The resulting figure has a vertical confidence bar at every value of X. It's kind of a cool effect and just as good, I guess, as the standard regression line plot with confidence bands. Thanks again Shige for pointing me in the right direction.cheers,Jason On Mon, Oct 17, 2011 11:36 AM, Shige Song <shiges...@gmail.com> wrote: > Hi Jason, > >I would go for Zelig package to get simulated values and confidence >intervals. It can handle gee model. > >Shige > >On Mon, Oct 17, 2011 at 9:38 AM, JASON M. HILL <jmh...@psu.edu> wrote: >> 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 >> >> >> >> >> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> R-help@r-project.org mailing list >> https://stat.ethz.ch/mailman/listinfo/r-help >> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html >> and provide commented, minimal, self-contained, reproducible code. >> > > >
'Nothing in biology makes sense, except in the light of evolution' --Theodosius Dobzhansky-- Jason Hill http://www.coopunits.org/Pennsylvania/People/Jason_Hill/index.html PA Cooperative Fish and Wildlife Research Unit 221 Forest Resources Building University Park, PA 16802-4705 Office: 814-865-0772 Fax: 814-863-4710 Ecology Program - PhD Candidate Pennsylvania State University School of Forest Resources [[alternative HTML version deleted]] ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
