medserial: Compute Power for Serial Mediation Effects Requires...

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

Compute Power for Serial Mediation Effects Requires correlations between all variables as sample size. This approach calculates power for the serial mediation using joint significance (recommended)

Description

Compute Power for Serial Mediation Effects Requires correlations between all variables as sample size. This approach calculates power for the serial mediation using joint significance (recommended)

Usage

medserial(rxm1, rxm2, rxy, rm1m2, rym1, rym2, n, alpha = 0.05, rep = 1000)

Arguments

rxm1	Correlation between predictor (x) and first mediator (m1)
rxm2	Correlation between predictor (x) and second mediator (m2)
rxy	Correlation between DV (y) and predictor (x)
rm1m2	Correlation first mediator (m1) and second mediator (m2)
rym1	Correlation between DV (y) and first mediator (m1)
rym2	Correlation between DV (y) and second mediator (m2)
n	sample size
alpha	Type I error (default is .05)
rep	number of repetitions (1000 is default)

Value

Power for Serial Mediated (Indirect) Effects

Examples

medserial(rxm1=.3, rxm2=.3, rxy=-.35,
rym1=-.5,rym2=-.5, rm1m2=.7,n=150)

pwr2ppl documentation built on Sept. 6, 2022, 5:06 p.m.