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

Description Usage Arguments Value Examples

View source: R/modmed14.R

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

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modmed14(
  rxw,
  rxm,
  rxxw,
  rxy,
  rwm = 0,
  rxww,
  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

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modmed14(rxw<-.2, rxm<-.3, rxxw=0, rxy=.31,rwm=.4,
rxww=0.5,rwy<-.35, rxwm<-.41, rxwy=.51,
rmy=.32, n=200, rep=1000,alpha=.05)

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