Package: InteractionPoweR 0.2.2
InteractionPoweR: Power Analyses for Interaction Effects in Cross-Sectional Regressions
Power analysis for regression models which test the interaction of two or three independent variables on a single dependent variable. Includes options for correlated interacting variables and specifying variable reliability. Two-way interactions can include continuous, binary, or ordinal variables. Power analyses can be done either analytically or via simulation. Includes tools for simulating single data sets and visualizing power analysis results. The primary functions are power_interaction_r2() and power_interaction() for two-way interactions, and power_interaction_3way_r2() for three-way interactions. Please cite as: Baranger DAA, Finsaas MC, Goldstein BL, Vize CE, Lynam DR, Olino TM (2023). "Tutorial: Power analyses for interaction effects in cross-sectional regressions." <doi:10.1177/25152459231187531>.
Authors:
InteractionPoweR_0.2.2.tar.gz
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InteractionPoweR.pdf |InteractionPoweR.html✨
InteractionPoweR/json (API)
NEWS
| # Install 'InteractionPoweR' in R: |
| install.packages('InteractionPoweR', repos = c('https://dbaranger.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/dbaranger/interactionpower/issues
- name_key - Name key for plotting
Last updated 4 months agofrom:5226f93c35. Checks:OK: 7. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 06 2024 |
| R-4.5-win | OK | Nov 06 2024 |
| R-4.5-linux | OK | Nov 06 2024 |
| R-4.4-win | OK | Nov 06 2024 |
| R-4.4-mac | OK | Nov 06 2024 |
| R-4.3-win | OK | Nov 06 2024 |
| R-4.3-mac | OK | Nov 06 2024 |
Exports:compute_adjustmentcor.mat.3waygenerate_interactiongenerate.interaction.cov.inputnorm2ordinalplot_interactionplot_power_curveplot_simple_slopepower_estimatepower_interactionpower_interaction_3way_r2power_interaction_r2power_interaction_r2_covssimple.slopes.3waytest_interaction
Dependencies:beeswarmbootchngptclicodetoolscolorspacecpp11doParalleldplyrfansifarverforeachgenericsggbeeswarmggplot2gluegtableisobanditeratorskyotillabelinglatticelifecyclelme4magrittrMASSMatrixmgcvminqamunsellnlmenloptrpillarpkgconfigpolynompurrrR6RColorBrewerRcppRcppEigenRhpcBLASctlrlangscalesstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviporviridisLitewithr
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| compute_adjustment | compute_adjustment |
| See the correlation matrix for a 3-way interaction | cor.mat.3way |
| Generate interaction data set | generate_interaction |
| Creates the input to 'power_interaction_r2_covs()' | generate.interaction.cov.input |
| Name key for plotting | name_key |
| norm2ordinal | norm2ordinal |
| Plot interaction | plot_interaction |
| Plot power curve | plot_power_curve |
| Simple slope plot | plot_simple_slope |
| Power estimate | power_estimate |
| Power analysis for interactions | power_interaction |
| Analytic power analysis for 3-way interactions | power_interaction_3way_r2 |
| Analytic power analysis for interactions | power_interaction_r2 |
| Analytic interaction power analysis with covariates | power_interaction_r2_covs |
| See the simple slopes for a 3-way interaction | simple.slopes.3way |
| Test interaction | test_interaction |
