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

In pwr2ppl: Power Analyses for Common Designs (Power to the People)

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

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

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

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 Sept. 6, 2022, 5:06 p.m.