Description Usage Arguments Value Examples

View source: R/MRC_shortcuts.R

Compute Multiple Regression shortcuts with three predictors (will expand to handle two to five) Requires correlations between all variables as sample size. Means and sds are option. Also computes Power(All)

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 |

`ry1` |
Correlation between DV (y) and first predictor (1) |

`ry2` |
Correlation between DV (y) and second predictor (2) |

`ry3` |
Correlation between DV (y) and third predictor (3) |

`r12` |
Correlation between first (1) and second predictor (2) |

`r13` |
Correlation between first (1) and third predictor (3) |

`r23` |
Correlation between second (2) and third predictor (3) |

`n` |
Sample size |

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

`my` |
Mean of DV (default is 0) |

`m1` |
Mean of first predictor (default is 0) |

`m2` |
Mean of second predictor (default is 0) |

`m3` |
Mean of third predictor (default is 0) |

`s1` |
Standard deviation of first predictor (default is 1) |

`s2` |
Standard deviation of second predictor (default is 1) |

`s3` |
Standard deviation of third predictor (default is 1) |

`sy` |
Standard deviation of DV (default is 1) |

Multiple Regression shortcuts with three predictors

1 2 | ```
MRC_shortcuts(ry1=.40,ry2=.40,ry3=-.40, r12=-.15, r13=-.60,r23=.25,
n=110, my=1,m1=1,m2=1,m3=1,sy=7,s1=1,s2=1,s3=2)
``` |

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