Recent statistical literature has paid attention to the presentation of pairwise comparisons either from the point of view of the reference category problem in generalized linear models (GLMs) or in terms of multiple comparisons. Both schools of thought are interested in the parsimonious presentation of sufficient information to enable readers to evaluate the significance of contrasts resulting from the inclusion of qualitative variables in GLMs. These comparisons also arise when trying to interpret multinomial models where one category of the dependent variable is omitted as a reference. While considerable advances have been made, opportunities remain to improve the presentation of this information, especially in graphical form. The factorplot package provides new functions for graphically and numerically presenting results of hypothesis tests related to pairwise comparisons resulting from qualitative covariates in GLMs or coefficients in multinomial logistic regression models.
multcomp, qvcalc, Epi, car, multcompView, factorplot
SocialSciences, Survival, ClinicalTrials, Econometrics, Finance, Multivariate
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For attribution, please cite this work as
II, "The R Journal: factorplot: Improving Presentation of Simple Contrasts in Generalized Linear Models", The R Journal, 2013
BibTeX citation
@article{RJ-2013-021,
author = {II, David A. Armstrong},
title = {The R Journal: factorplot: Improving Presentation of Simple Contrasts in Generalized Linear Models},
journal = {The R Journal},
year = {2013},
note = {https://doi.org/10.32614/RJ-2013-021},
doi = {10.32614/RJ-2013-021},
volume = {5},
issue = {2},
issn = {2073-4859},
pages = {4-15}
}