# MRC: Compute power for Multiple Regression with up to Five... In pwr2ppl: Power Analyses for Common Designs (Power to the People)

## Description

Compute power for Multiple Regression with up to Five Predictors Example code below for three predictors. Expand as needed for four or five

## Usage

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19``` ```MRC( ry1 = NULL, ry2 = NULL, ry3 = NULL, ry4 = NULL, ry5 = NULL, r12 = NULL, r13 = NULL, r14 = NULL, r15 = NULL, r23 = NULL, r24 = NULL, r25 = NULL, r34 = NULL, r35 = NULL, r45 = NULL, n = NULL, alpha = 0.05 ) ```

## Arguments

 `ry1` Correlation between DV (y) and first predictor (1) `ry2` Correlation between DV (y) and second predictor (2) `ry3` Correlation between DV (y) and third predictor (3) `ry4` Correlation between DV (y) and fourth predictor (4) `ry5` Correlation between DV (y) and fifth predictor (5) `r12` Correlation between first (1) and second predictor (2) `r13` Correlation between first (1) and third predictor (3) `r14` Correlation between first (1) and fourth predictor (4) `r15` Correlation between first (1) and fifth predictor (5) `r23` Correlation between second (2) and third predictor (3) `r24` Correlation between second (2) and fourth predictor (4) `r25` Correlation between second (2) and fifth predictor (5) `r34` Correlation between third (3) and fourth predictor (4) `r35` Correlation between third (3) and fifth predictor (5) `r45` Correlation between fourth (4) and fifth predictor (5) `n` Sample size `alpha` Type I error (default is .05)

## Value

Power for Multiple Regression with Two to Five Predictors

## Examples

 ```1 2``` ```MRC(ry1=.40,ry2=.40, r12=-.15,n=30) MRC(ry1=.40,ry2=.40,ry3=-.40, r12=-.15, r13=-.60,r23=.25,n=24) ```

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