Package: Superpower 0.2.2

Superpower: Simulation-Based Power Analysis for Factorial Designs

Functions to perform simulations of ANOVA designs of up to three factors. Calculates the observed power and average observed effect size for all main effects and interactions in the ANOVA, and all simple comparisons between conditions. Includes functions for analytic power calculations and additional helper functions that compute effect sizes for ANOVA designs, observed error rates in the simulations, and functions to plot power curves. Please see Lakens, D., & Caldwell, A. R. (2021). "Simulation-Based Power Analysis for Factorial Analysis of Variance Designs". <doi:10.1177/2515245920951503>.

Authors:Aaron Caldwell [aut, cre], Daniel Lakens [aut], Lisa DeBruine [ctb], Jonathon Love [ctb], Frederik Aust [ctb]

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Superpower.pdf |Superpower.html✨
Superpower/json (API)
NEWS

# Install 'Superpower' in R:
install.packages('Superpower', repos = c('https://arcaldwell49.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/arcaldwell49/superpower/issues

On CRAN:

23 exports 65 stars 3.73 score 66 dependencies 1 dependents 2 mentions 114 scripts 386 downloads

Last updated 2 years agofrom:ed624538f6. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 03 2024
R-4.5-winNOTESep 03 2024
R-4.5-linuxNOTESep 03 2024
R-4.4-winOKSep 03 2024
R-4.4-macOKSep 03 2024
R-4.3-winOKSep 03 2024
R-4.3-macOKSep 03 2024

Exports:alpha_standardizedANCOVA_analyticANCOVA_contrastANOVA_compromiseANOVA_designANOVA_exactANOVA_exact2ANOVA_poweremmeans_powermorey_plot.ftestmorey_plot.ttestmu_from_ESoptimal_alphap_standardizedplot_powerpower_oneway_ancovapower_oneway_betweenpower_oneway_withinpower_standardized_alphapower_threeway_betweenpower_twoway_betweenpower.ftestSuperpower_options

Dependencies:abindafexbackportsbootbroomcarcarDataclicolorspacecowplotcpp11DerivdoBydplyremmeansestimabilityfansifarvergenericsggplot2gluegtableisobandlabelinglatticelifecyclelme4lmerTestmagrittrMASSMatrixMatrixModelsmgcvmicrobenchmarkminqamodelrmunsellmvtnormnlmenloptrnnetnumDerivpbkrtestpillarpkgconfigplyrpurrrquantregR6RColorBrewerRcppRcppEigenreshape2rlangscalesSparseMstringistringrsurvivaltibbletidyrtidyselectutf8vctrsviridisLitewithr

Introduction to Justifying Alpha Levels

Daniel Lakens & Aaron R. Caldwell

Rendered fromcompromise_power.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2021-03-19
Started: 2020-08-26

Introduction to Superpower

Daniel Lakens & Aaron R. Caldwell

Rendered fromintro_to_superpower.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2021-12-09
Started: 2019-09-06

More ANOVA designs

Aaron R. Caldwell

Rendered frommore_anova_designs.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2021-12-09
Started: 2021-03-19

Power calculations for emmeans analyses

Frederik Aust

Rendered fromemmeans_power.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2021-12-09
Started: 2020-04-22

Power Calculations for ANCOVA

Aaron R. Caldwell

Rendered fromANCOVAs.Rmdusingknitr::rmarkdownon Sep 03 2024.

Last update: 2022-05-16
Started: 2021-12-09

Readme and manuals

Help Manual

Help pageTopics
Compute standardized alpha level based on unstandardized alpha level and the number of observations N.alpha_standardized
Power Calculations for Factorial ANCOVAsANCOVA_analytic
Power Calculations for ANCOVA ContrastsANCOVA_contrast
Methods for ancova_power objectsancova_power-methods plot.ancova_power print.ancova_power
Justify your alpha level by minimizing or balancing Type 1 and Type 2 error rates for ANOVAs.ANOVA_compromise
Design function used to specify the parameters to be used in simulationsANOVA_design
Simulates an exact dataset (mu, sd, and r represent empirical, not population, mean and covariance matrix) from the design to calculate powerANOVA_exact ANOVA_exact2
Simulation function used to estimate powerANOVA_power
Methods for design_aov objectsdesign_aov-methods plot.design_aov print.design_aov
Compute power for 'emmeans' contrastsemmeans_power emmeans_power.data.frame emmeans_power.emmGrid emmeans_power.summary_em
Plot out power sensitivity plots for t or F testsmorey_plot.ftest morey_plot.ttest
Convenience function to calculate the means for between designs with one factor (One-Way ANOVA). Can be used to determine the means that should yield a specified effect sizes (expressed in Cohen's f).mu_from_ES
Methods for opt_alpha objectsopt_alpha-methods plot.opt_alpha print.opt_alpha
Justify your alpha level by minimizing or balancing Type 1 and Type 2 error rates.optimal_alpha
Compute standardized alpha level based on unstandardized alpha level and the number of observations N.p_standardized
Convenience function to plot power across a range of sample sizes.plot_power
Power Calculations for a one-way ANCOVApower_oneway_ancova
Analytic power calculation for one-way between designs.power_oneway_between
Analytic power calculation for one-way within designs.power_oneway_within
Optimizing function to achieve desired power based on a standardized alpha level.power_standardized_alpha
Analytic power calculation for three-way between designs.power_threeway_between
Analytic power calculation for two-way between designs.power_twoway_between
Power Calculations for an F-testpower.ftest
Methods for sim_result objectsconfint.sim_result plot.sim_result print.sim_result sim_result-methods
Set/get global Superpower optionsSuperpower_options