power_interaction_r2_covs {InteractionPoweR} | R Documentation |
Analytic interaction power analysis with covariates
Description
Analytic power analysis of an interaction model with covariates. Additional covariate x main effect interaction terms are additionally added.
Usage
power_interaction_r2_covs(
cov.input,
N,
alpha = 0.05,
detailed_results = FALSE,
cl = NULL
)
Arguments
cov.input |
Output of 'power_interaction_r2_covs()'. Variable correlations and reliabilities are set by first modifying this list. |
N |
Sample size. Must be a positive integer. Has no default value. Can be a single value or a vector of values. |
alpha |
The alpha. At what p-value is the interaction deemed significant? Default is 0.05. |
detailed_results |
Default is FALSE. Should detailed results be reported? |
cl |
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. |
Value
A data frame containing the analytic power for each unique setting combination.
Examples
ex1 = generate.interaction.cov.input(c.num=2)
ex1$correlations$r.y.x1x2 = c(0.1,0.2,0.3)
power_interaction_r2_covs(cov.input = ex1,N=100)
[Package InteractionPoweR version 0.2.2 Index]