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

Description Usage Arguments Value Examples

View source: R/medserial.R

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

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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

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

Example output

Power for n = 150, mediator 1 is 0.735
Power for n = 150, mediator 2 is 0.272
Power for n = 150, serial mediation is 0.721

pwr2ppl documentation built on April 4, 2021, 9:06 a.m.