Description Usage Arguments Value Examples

Compute Power for Serial Mediation Effects Requires correlations between all variables as sample size. This approach calculates power for the serial mediation using joint significance (recommended)

1 |

`rxm1` |
Correlation between predictor (x) and first mediator (m1) |

`rxm2` |
Correlation between predictor (x) and second mediator (m2) |

`rxy` |
Correlation between DV (y) and predictor (x) |

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

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

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

`n` |
sample size |

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

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

Power for Serial Mediated (Indirect) Effects

1 2 | ```
medserial(rxm1=.3, rxm2=.3, rxy=-.35,
rym1=-.5,rym2=-.5, rm1m2=.7,n=150)
``` |

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