# modmed7: Compute Power for Model 7 Conditional Processes Using Joint... In pwr2ppl: Power Analyses for Common Designs (Power to the People)

## Description

Compute Power for Model 7 Conditional Processes Using Joint Significance Requires correlations between all variables as sample size. This is the recommended approach for determining power

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15``` ```modmed7( rxm, rxw, rxxw, rxy, rwm, rwxw, rwy = 0, rmxw, rmy, rxwy = 0, alpha = 0.05, rep = 1000, n = NULL ) ```

## Arguments

 `rxm` Correlation between predictor (x) and mediator (m) `rxw` Correlation between predictor (x) and moderator (w) `rxxw` Correlation between predictor (x) and interaction term (xw) - defaults to 0 `rxy` Correlation between DV (y) and predictor (x) `rwm` Correlation between moderator (w) and mediator (m) `rwxw` Correlation between moderator (w) and interaction (xw) - defaults to 0 `rwy` Correlation between DV (y) and moderator (w) `rmxw` Correlation between mediator (m) and interaction (xw) - Key value `rmy` Correlation between DV (y) and mediator (m) `rxwy` Correlation between DV (y) and interaction (xw) - defaults to 0 `alpha` Type I error (default is .05) `rep` Number of samples drawn (defaults to 5000) `n` Sample size

## Value

Power for Model 7 Conditional Processes

## Examples

 ```1 2``` ```modmed7(rxm=.4, rxw=.3, rxxw=.01, rxy=.50, rmy=.31, rxwy=.02,rwm=.45, rwy=.2,rmxw = .24, rwxw=.21, alpha=.05,rep=1000,n=400) ```

pwr2ppl documentation built on April 4, 2021, 9:06 a.m.