Compute and plot predictions, slopes, marginal means, and comparisons (contrasts, risk ratios, odds, etc.) for over 100 classes of statistical and machine learning models in R. Conduct linear and non-linear hypothesis tests, or equivalence tests. Calculate uncertainty estimates using the delta method, bootstrapping, or simulation-based inference. Details can be found in Arel-Bundock, Greifer, and Heiss (2024) <doi:10.18637/jss.v111.i09>.
| Reference manual: | marginaleffects.html , marginaleffects.pdf |
| Vignettes: |
Model to Meaning (source, R code) |
| Package source: | marginaleffects_0.32.0.tar.gz |
| Windows binaries: | r-devel: marginaleffects_0.32.0.zip, r-release: marginaleffects_0.32.0.zip, r-oldrel: marginaleffects_0.32.0.zip |
| macOS binaries: | r-release (arm64): marginaleffects_0.32.0.tgz, r-oldrel (arm64): marginaleffects_0.32.0.tgz, r-release (x86_64): marginaleffects_0.32.0.tgz, r-oldrel (x86_64): marginaleffects_0.32.0.tgz |
| Old sources: | marginaleffects archive |
| Reverse imports: | adrftools, bsitar, clarify, dotwhisker, etwfe, ggfixest, healthequal, mvgam, pminternal, psre, SynergyLMM |
| Reverse suggests: | bayestestR, beeca, broom.helpers, catregs, DAGassist, DeclareDesign, descriptio, easystats, ggeffects, gratia, insight, lmw, MatchIt, modelbased, modelsummary, optweight, ordbetareg, outstandR, parameters, rdss, report, see, statuser, tinytable, VizTest, WeightIt |
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