Heymans, M.W. wrote:> Hi all,
>
> I have fitted a gee model with the gee package and included restricted
cubic spline functions. Here is the model:
>
> chol.g <- gee(SKIN ~ rcs(CHOLT, 3), id=ID, data=chol,
family=binomial(link="logit"), corstr="exchangeable")
>
> To extract the log odds I use:
>
> predict.glm(chol.g, type = "link")
I wonder if such predictions are 'safe', i.e., use the original knot
locations hidden in an attribute by rcs.
>
> Now I want to compute the logg odds for specific CHOLT values (the
dependent variable) that I want to choose myself (i.e. that are not available in
the dataset). Is there a way to get the linear predictor of the gee model
including all separate spline functions and related coefficients? Latex from the
Design package does not work here.
You'll either need to write a wrapper function for gee like glmD is for
glm, or use lrm in Design with intra-cluster correlation correction
using robcov or bootcov. However this would assume a working
independence model rather than a compound symmetry working model.
Frank
>
> Thanks for your help!
>
> kind regards,
>
> Martijn W Heymans
>
> Faculty of Earth and Life Sciences
>
> Institute of Health Sciences
>
> Department of Methodology and Applied Biostatistics
> VU University
>
> Amsterdam, the Netherlands
>
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>
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--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University