pwr2ppl (version 0.5.0)

med: Compute Power for Mediated (Indirect) Effects Requires correlations between all variables as sample size. This approach calculates power for the Sobel test. The medjs function calculates power based on joint significance (recommended)

Description

Compute Power for Mediated (Indirect) Effects Requires correlations between all variables as sample size. This approach calculates power for the Sobel test. The medjs function calculates power based on joint significance (recommended)

Usage

med(
  rxm1,
  rxm2 = 0,
  rxm3 = 0,
  rxm4 = 0,
  rxy,
  rym1,
  rym2 = 0,
  rym3 = 0,
  rym4 = 0,
  rm1m2 = 0,
  rm1m3 = 0,
  rm1m4 = 0,
  rm2m3 = 0,
  rm2m4 = 0,
  rm3m4 = 0,
  alpha = 0.05,
  mvars,
  n
)

Value

Power for Mediated (Indirect) Effects

Arguments

rxm1

Correlation between predictor (x) and first mediator (m1)

rxm2

Correlation between predictor (x) and second mediator (m2)

rxm3

Correlation between predictor (x) and third mediator (m3)

rxm4

Correlation between predictor (x) and fourth mediator (m4)

rxy

Correlation between DV (y) and predictor (x)

rym1

Correlation between DV (y) and first mediator (m1)

rym2

Correlation between DV (y) and second mediator (m2)

rym3

Correlation DV (y) and third mediator (m3)

rym4

Correlation DV (y) and fourth mediator (m4)

rm1m2

Correlation first mediator (m1) and second mediator (m2)

rm1m3

Correlation first mediator (m1) and third mediator (m3)

rm1m4

Correlation first mediator (m1) and fourth mediator (m4)

rm2m3

Correlation second mediator (m2) and third mediator (m3)

rm2m4

Correlation second mediator (m2) and fourth mediator (m4)

rm3m4

Correlation third mediator (m3) and fourth mediator (m4)

alpha

Type I error (default is .05)

mvars

Number of Mediators

n

Sample size

Examples

med(rxm1=.25, rxy=-.35, rym1=-.5,mvars=1, n=150)
med(rxm1=.3, rxm2=.3, rxm3=.25, rxy=-.35, rym1=-.5,rym2=-.5, rym3 = -.5,
rm1m2=.7, rm1m3=.4,rm2m3=.4, mvars=3, n=150)