We introduce a new R package called glmperm for inference in generalized linear models especially for small and moderate-sized data sets. The inference is based on the permutation of regressor residuals test introduced by Potter (2005). The implementation of glmperm outperforms currently available permutation test software as glmperm can be applied in situations where more than one covariate is involved.
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For attribution, please cite this work as
Werft & Benner, "The R Journal: glmperm: A Permutation of Regressor Residuals Test for Inference in Generalized Linear Models", The R Journal, 2010
BibTeX citation
@article{RJ-2010-007,
author = {Werft, Wiebke and Benner, Axel},
title = {The R Journal: glmperm: A Permutation of Regressor Residuals Test for Inference in Generalized Linear Models},
journal = {The R Journal},
year = {2010},
note = {https://doi.org/10.32614/RJ-2010-007},
doi = {10.32614/RJ-2010-007},
volume = {2},
issue = {1},
issn = {2073-4859},
pages = {39-43}
}