modmed7: Compute Power for Model 7 Conditional Processes Using Joint...

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

Compute Power for Model 7 Conditional Processes Using Joint Significance Requires correlations between all variables as sample size Several values default to zero if no value provided This is the recommended approach for determining power

Description

Compute Power for Model 7 Conditional Processes Using Joint Significance Requires correlations between all variables as sample size Several values default to zero if no value provided This is the recommended approach for determining power

Usage

modmed7(
  rxm,
  rxw,
  rxxw = 0,
  rxy,
  rwm,
  rwxw = 0,
  rwy = 0,
  rmxw,
  rmy,
  rxwy = 0,
  alpha = 0.05,
  rep = 1000,
  n = NULL
)

Arguments

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

Value

Power for Model 7 Conditional Processes

Examples

modmed7(rxm=.4, rxw=.2, rxy=.3, rwm=.2, rmxw=.1, rmy=.3,n=200)

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