# modmed14: Compute Power for Conditional Process Model 14 Joint... In pwr2ppl: Power Analyses for Common Designs (Power to the People)

## Description

Compute Power for Conditional Process Model 14 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``` ```modmed14( rxw, rxm, rxxw, rxy, rwm = 0, rxww, rwy, rxwm = 0, rxwy, 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 xweraction term (xw) - defaults to 0 `rxy` Correlation between DV (y) and predictor (x) `rwm` Correlation between moderator (w) and mediator (m) `rxww` Correlation between moderator (w) and xweraction (xw) - defaults to 0 `rwy` Correlation between DV (y) and moderator (w) `rxwm` Correlation between mediator (m) and xweraction (xw) - Key value `rxwy` Correlation between DV (y) and xweraction (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 14 Conditional Processes

## Examples

 ```1 2 3``` ```modmed14(rxw<-.2, rxm<-.3, rxxw=0, rxy=.31,rwm=.4, rxww=0.5,rwy<-.35, rxwm<-.41, rxwy=.51, rmy=.32, n=200, rep=1000,alpha=.05) ```

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