MRC_all {pwr2ppl}

Compute power for Multiple Regression with Up to Five Predictors Requires correlations between all variables as sample size. Means, sds, and alpha are option. Also computes Power(All)

Description

Compute power for Multiple Regression with Up to Five Predictors Requires correlations between all variables as sample size. Means, sds, and alpha are option. Also computes Power(All)

Usage

MRC_all(
  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,
  rep = 10000
)

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)

rep

number of replications (default is 10000)

Value

Power for Multiple Regression (ALL)

Examples

MRC_all(ry1=.50,ry2=.50,ry3=.50, r12=.2, r13=.3,r23=.4,n=82, rep=10000)