modmed7 {pwr2ppl}

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)