modmed14: Compute Power for Conditional Process Model 14 Joint...

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

Compute Power for Conditional Process Model 14 Joint Significance Requires correlations between all variables as sample size. This is the recommended approach for determining power

Description

Compute Power for Conditional Process Model 14 Joint Significance Requires correlations between all variables as sample size. This is the recommended approach for determining power

Usage

modmed14(
  rxw,
  rxm,
  rxxw = 0,
  rxy,
  rwm = 0,
  rxww = 0,
  rwy,
  rxwm = 0,
  rxwy,
  rmy,
  n,
  alpha = 0.05,
  rep = 5000
)

Arguments

rxw	Correlation between predictor (x) and moderator (w)
rxm	Correlation between predictor (x) and mediator (m)
rxxw	Correlation between predictor (x) and xweraction term (xw) - defaults to 0
rxy	Correlation between DV (y) and predictor (x)
rwm	Correlation between moderator (w) and mediator (m)
rxww	Correlation between moderator (w) and xweraction (xw) - defaults to 0
rwy	Correlation between DV (y) and moderator (w)
rxwm	Correlation between mediator (m) and xweraction (xw) - Key value
rxwy	Correlation between DV (y) and xweraction (xw) - defaults to 0
rmy	Correlation between DV (y) and mediator (m)
n	Sample size
alpha	Type I error (default is .05)
rep	Number of samples drawn (defaults to 5000)

Value

Power for Model 14 Conditional Processes

Examples

modmed14(rxw=.2, rxm=.2, rxy=.31,rwy=.35, rxwy=.2,
rmy=.32, n=200, rep=1000,alpha=.05)

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