power_interaction_r2_covs

Analytic power analysis of an interaction model with covariates. Additional covariate x main effect interaction terms are additionally added.

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

power_interaction_r2_covs function

<dl><dt>cov.input</dt>
<dd>Output of 'power_interaction_r2_covs()'. Variable correlations and reliabilities are set by first modifying this list.</dd>
<dt>N</dt>
<dd>Sample size. Must be a positive integer. Has no default value. Can be a single value or a vector of values.</dd>
<dt>alpha</dt>
<dd>The alpha. At what p-value is the interaction deemed significant? Default is 0.05.</dd>
<dt>detailed_results</dt>
<dd>Default is FALSE. Should detailed results be reported?</dd>
<dt>cl</dt>
<dd>Number of clusters to use for running simulations in parallel. Default is NULL (i.e. not in parallel). Useful when running several thousand analyses at once.</dd></dl>

Arguments

Analytic interaction power analysis with covariates — power_interaction_r2_covs

<dl>

<dt>cov.input</dt>
<dd>Output of 'power_interaction_r2_covs()'. Variable correlations and reliabilities are set by first modifying this list.</dd>


<dt>N</dt>
<dd>Sample size. Must be a positive integer. Has no default value. Can be a single value or a vector of values.</dd>


<dt>alpha</dt>
<dd>The alpha. At what p-value is the interaction deemed significant? Default is 0.05.</dd>


<dt>detailed_results</dt>
<dd>Default is FALSE. Should detailed results be reported?</dd>


<dt>cl</dt>
<dd>Number of clusters to use for running simulations in parallel. Default is NULL (i.e. not in parallel). Useful when running several thousand analyses at once.</dd>

</dl>

power_interaction_r2_covs: Analytic interaction power analysis with covariates

Description

Usage

Value

Arguments

Examples