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
[[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.
--
Frank E Harrell Jr Professor and Chair School of Medicine
Department of Biostatistics Vanderbilt University
______________________________________________
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.
