# modmed8: Compute Power for Power for Model 8 Conditional Processes... In pwr2ppl: Power Analyses for Common Designs (Power to the People)

## Description

Compute Power for Power for Model 8 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``` ```modmed8( rxw, rxm, rxxw, rxy, rwm = 0, rwy, rxwm, rxwy, rwxw, rmy, n, alpha = 0.05, rep = 5000 ) ```

## Arguments

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

## Value

Power for Model 8 Conditional Processes

## Examples

 ```1 2``` ```modmed8(rxw<-.21, rxm<-.31, rxxw=0, rxy=.32,rwm=.40, rmy=.19,rwy=.22,rwxw=.23,rxwm=.24,rxwy=.18,alpha=.05,rep=1000,n=400) ```

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