MRC: Compute power for Multiple Regression with up to Five...

Description Usage Arguments Value Examples

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

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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

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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 June 12, 2019, 5:03 p.m.