power_interaction_r2 {InteractionPoweR}

Analytic power analysis for interactions

Description

Power analysis for interaction models, computed via change in R2. Valid for interactions with continuous, normally distributed, variables.

Usage

power_interaction_r2(
  N,
  r.x1.y,
  r.x2.y,
  r.x1x2.y,
  r.x1.x2,
  rel.x1 = 1,
  rel.x2 = 1,
  rel.y = 1,
  alpha = 0.05,
  detailed_results = FALSE
)

Arguments

N

Sample size. Must be a positive integer. Has no default value. Can be a single value or a vector of values.

r.x1.y

Pearson's correlation between x1 and y. Must be between -1 and 1. Has no default value. Can be a single value or a vector of values.

r.x2.y

Pearson's correlation between x2 and y. Must be between -1 and 1. Assumed to be the 'moderator' in some functions. Has no default value. Can be a single value or a vector of values.

r.x1x2.y

Pearson's correlation between the interaction term x1x2 (x1 * x2) and y. Must be between -1 and 1. Has no default value. Can be a single value or a vector of values.

r.x1.x2

Pearson's correlation between x1 and x2. Must be between -1 and 1. Has no default value. Can be a single value or a vector of values.

rel.x1

Reliability of x1 (e.g. test-retest reliability, ICC, Cronbach's alpha). Default is 1 (perfect reliability). Must be greater than 0 and less than or equal to 1.

rel.x2

Reliability of x2 (e.g. test-retest reliability, ICC, Cronbach's alpha). Default is 1 (perfect reliability). Must be greater than 0 and less than or equal to 1.

rel.y

Reliability of xy (e.g. test-retest reliability, ICC, Cronbach's alpha). Default is 1 (perfect reliability). Must be greater than 0 and less than or equal to 1.

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?

Value

A data frame containing the power for each unique setting combination.

Examples

power_interaction_r2(N=seq(100,300,by=10),r.x1.y=0.2, r.x2.y=.2,r.x1x2.y=0.2,r.x1.x2=.2)