Generalized estimating equation solvers in R only allow for a few pre-determined options for the link and variance functions. We provide a package, geeM, which is implemented entirely in R and allows for user specified link and variance functions. The sparse matrix representations provided in the Matrix package enable a fast implementation. To gain speed, we make use of analytic inverses of the working correlation when possible and a trick to find quick numeric inverses when an analytic inverse is not available. Through three examples, we demonstrate the speed of geeM, which is not much worse than C implementations like geepack and gee on small data sets and faster on large data sets.
Econometrics, SocialSciences, Multivariate, NumericalMathematics
Text and figures are licensed under Creative Commons Attribution CC BY 4.0. The figures that have been reused from other sources don't fall under this license and can be recognized by a note in their caption: "Figure from ...".
For attribution, please cite this work as
McDaniel, et al., "The R Journal: Fast Pure R Implementation of GEE: Application of the Matrix Package", The R Journal, 2013
BibTeX citation
@article{RJ-2013-017,
author = {McDaniel, Lee S. and Henderson, Nicholas C. and Rathouz, Paul J.},
title = {The R Journal: Fast Pure R Implementation of GEE: Application of the Matrix Package},
journal = {The R Journal},
year = {2013},
note = {https://doi.org/10.32614/RJ-2013-017},
doi = {10.32614/RJ-2013-017},
volume = {5},
issue = {1},
issn = {2073-4859},
pages = {181-187}
}