Plotting interactions | Plotting observed data | Plotting partial residuals | Confidence bands | Check linearity assumption | Other options | Simple slopes analysis and Johnson-Neyman intervals | Visualize the coefficients | Tabular output | Johnson-Neyman intervals | False discovery rate adjustment | Additional options | Conditional intercepts | Robust standard errors | Centering variables | Do simple slopes and plotting with one function | 3-way interactions | Generalized linear models, mixed models, et al. | References
Package: interactions 1.2.0
interactions: Comprehensive, User-Friendly Toolkit for Probing Interactions
A suite of functions for conducting and interpreting analysis of statistical interaction in regression models that was formerly part of the 'jtools' package. Functionality includes visualization of two- and three-way interactions among continuous and/or categorical variables as well as calculation of "simple slopes" and Johnson-Neyman intervals (see e.g., Bauer & Curran, 2005 <doi:10.1207/s15327906mbr4003_5>). These capabilities are implemented for generalized linear models in addition to the standard linear regression context.
Authors:
interactions_1.2.0.tar.gz
interactions_1.2.0.zip(r-4.7)interactions_1.2.0.zip(r-4.6)interactions_1.2.0.zip(r-4.5)
interactions_1.2.0.tgz(r-4.6-any)interactions_1.2.0.tgz(r-4.5-any)
interactions_1.2.0.tar.gz(r-4.7-any)interactions_1.2.0.tar.gz(r-4.6-any)
interactions_1.2.0.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
DESCRIPTION |NEWS
card.svg |card.png
interactions/json (API)
| # Install 'interactions' in R: |
| install.packages('interactions', repos = c('https://jacob-long.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/jacob-long/interactions/issues
Pkgdown/docs site:https://interactions.jacob-long.com
interactionsmoderationsocial-sciencesstatistics
Last updated from:df22b3ddcf. Checks:7 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-x86_64 | NOTE | 281 | ||
| source / vignettes | OK | 239 | ||
| linux-release-x86_64 | NOTE | 277 | ||
| macos-release-arm64 | NOTE | 185 | ||
| macos-oldrel-arm64 | NOTE | 176 | ||
| windows-devel | NOTE | 228 | ||
| windows-release | NOTE | 242 | ||
| windows-oldrel | NOTE | 222 | ||
| wasm-release | OK | 171 |
Exports:cat_plotglanceinteract_plotjohnson_neymanprobe_interactionsim_marginssim_slopestidy
Dependencies:backportsbroombroom.mixedclicodacodetoolscpp11digestdplyrfarverforcatsfurrrfuturegenericsggplot2globalsgluegtableisobandjtoolslabelinglatticelifecyclelistenvmagrittrnlmepanderparallellypillarpkgconfigpurrrR6RColorBrewerRcpprlangS7sandwichscalesstringistringrtibbletidyrtidyselectutf8vctrsviridisLitewithrzoo
Exploring interactions with continuous predictors in regression models
Last update: 2022-04-10
Started: 2017-02-03
Plotting interactions among categorical variables in regression models
Simple two-way interaction | Line plots | Bar/dynamite plots
Last update: 2022-04-10
Started: 2017-11-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Create tabular output for simple margins analysis | as_huxtable.sim_margins |
| Create tabular output for simple slopes analysis | as_huxtable.sim_slopes |
| Plot interaction effects between categorical predictors. | cat_plot |
| Plot interaction effects in regression models | interact_plot |
| Calculate Johnson-Neyman intervals for 2-way interactions | johnson_neyman |
| Plot coefficients from simple slopes analysis | plot.sim_margins |
| Plot coefficients from simple slopes analysis | plot.sim_slopes |
| Probe interaction effects via simple slopes and plotting | probe_interaction |
| Perform a simple margins analysis. | sim_margins |
| Perform a simple slopes analysis. | sim_slopes |
| Tidiers for 'sim_margins()' objects. | glance.sim_margins tidy.sim_margins |
| Tidiers for 'sim_slopes()' objects. | glance.sim_slopes tidy.sim_slopes |
