name_key

<p>Expanded variable names so that plots look nicer.</p>

Power analysis for regression models which test the interaction of
two independent variables on a single dependent variable. Includes options
for continuous, binary, or ordinal variables, as well as correlated
interacting variables. Also includes options to specify variable reliability.
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().
Please cite as: Baranger DAA, Finsaas MC, Goldstein BL, Vize CE, Lynam DR,
Olino TM (2022). "Tutorial: Power analyses for interaction effects in
cross-sectional regressions." <doi:10.31234/osf.io/5ptd7>.

David Baranger

InteractionPoweR

Power Analyses for Interaction Effects in Cross-Sectional
Regressions

Brandon Goldstein

Megan Finsaas

Thomas Olino

Colin Vize

Don Lynam

name_key function

<p>A data frame with 25 rows and 2 variables</p>

Format

Name key for plotting — name_key

Name key for plotting

name_key: Name key for plotting

Description

Usage

Arguments

Format