generate.interaction.cov.input

Companion function to 'power_interaction_r2_covs()'. Generates a formatted list for users to specify the analysis parameters.

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>.

David Baranger

InteractionPoweR

Power Analyses for Interaction Effects in Cross-Sectional
Regressions

Brandon Goldstein

Megan Finsaas

Thomas Olino

Colin Vize

Don Lynam

generate.interaction.cov.input function

<dl><dt>c.num</dt>
<dd>Number of covariates in the model.</dd></dl>

Arguments

Creates the input to power_interaction_r2_covs() — generate.interaction.cov.input

<dl>

<dt>c.num</dt>
<dd>Number of covariates in the model.</dd>

</dl>

generate.interaction.cov.input: Creates the input to `power_interaction_r2_covs()`

Description

Usage

Value

Arguments

Examples