medjs | R Documentation |

Compute Power for Mediated (Indirect) Effects Using Joint Significance Requires correlations between all variables as sample size. This is the recommended approach for determining power

medjs( rx1x2 = NULL, rx1m1, rx1m2 = NULL, rx1m3 = NULL, rx1m4 = NULL, rx1y, rx2m1 = NULL, rx2m2 = NULL, rx2m3 = NULL, rx2m4 = NULL, rx2y, rym1, rym2 = NULL, rym3 = NULL, rym4 = NULL, rm1m2 = NULL, rm1m3 = NULL, rm1m4 = NULL, rm2m3 = NULL, rm2m4 = NULL, rm3m4 = NULL, n, alpha = 0.05, mvars, rep = 1000, pred = 1 )

`rx1x2` |
Correlation between first predictor (x1) and second predictor (x2) |

`rx1m1` |
Correlation between first predictor (x1) and first mediator (m1) |

`rx1m2` |
Correlation between first predictor (x1) and second mediator (m2) |

`rx1m3` |
Correlation between first predictor (x1) and third mediator (m3) |

`rx1m4` |
Correlation between first predictor (x1) and fourth mediator (m4) |

`rx1y` |
Correlation between DV (y) and first predictor (x1) |

`rx2m1` |
Correlation between second predictor (x2) and first mediator (m1) |

`rx2m2` |
Correlation between second predictor (x2) and second mediator (m2) |

`rx2m3` |
Correlation between second predictor (x2) and third mediator (m3) |

`rx2m4` |
Correlation between second predictor (x2) and fourth mediator (m4) |

`rx2y` |
Correlation between DV (y) and second predictor (x2) |

`rym1` |
Correlation between DV (y) and first mediator (m1) |

`rym2` |
Correlation between DV (y) and second mediator (m2) |

`rym3` |
Correlation DV (y) and third mediator (m3) |

`rym4` |
Correlation DV (y) and fourth mediator (m4) |

`rm1m2` |
Correlation first mediator (m1) and second mediator (m2) |

`rm1m3` |
Correlation first mediator (m1) and third mediator (m3) |

`rm1m4` |
Correlation first mediator (m1) and fourth mediator (m4) |

`rm2m3` |
Correlation second mediator (m2) and third mediator (m3) |

`rm2m4` |
Correlation second mediator (m2) and fourth mediator (m4) |

`rm3m4` |
Correlation third mediator (m3) and fourth mediator (m4) |

`n` |
Sample size |

`alpha` |
Type I error (default is .05) |

`mvars` |
Number of Mediators |

`rep` |
number of repetitions (1000 is default) |

`pred` |
number of predictors (default is one) |

Power for Mediated (Indirect) Effects

medjs(rx1m1=.3, rx1m2=.3, rx1m3=.25, rx1y=-.35, rym1=-.5,rym2=-.5, rym3 = -.5, rm1m2=.7, rm1m3=.4,rm2m3=.4, mvars=3, n=150)

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