Description Usage Arguments Value Author(s) See Also Examples

The textbook Quasi-F test for a design with subjects, items, and a single factorial predictor. Included for educational purposes for this specific design only.

1 | ```
quasiF.fnc(ms1, ms2, ms3, ms4, df1, df2, df3, df4)
``` |

`ms1` |
Mean squares Factor |

`ms2` |
Mean squares Item:Subject |

`ms3` |
Mean squares Factor:Subject |

`ms4` |
Mean squares Item |

`df1` |
Degrees of freedom Factor |

`df2` |
Degrees of freedom Item:Subject |

`df3` |
Degrees of freedom Factor:Subject |

`df4` |
Degrees of freedom Item |

A list with components

`F ` |
Quasi-F value. |

`df1` |
degrees of freedom numerator. |

`df2` |
degrees of freedom denominator. |

`p` |
p-value. |

R. H. Baayen

See Also as `quasiFsim.fnc`

.

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 | ```
data(quasif)
quasif.lm = lm(RT ~ SOA + Item + Subject +
SOA:Subject + Item:Subject, data = quasif)
quasif.aov = anova(quasif.lm)
quasiF.fnc(quasif.aov["SOA","Mean Sq"],
quasif.aov["Item:Subject", "Mean Sq"],
quasif.aov["SOA:Subject", "Mean Sq"],
quasif.aov["Item", "Mean Sq"],
quasif.aov["SOA","Df"],
quasif.aov["Item:Subject", "Df"],
quasif.aov["SOA:Subject", "Df"],
quasif.aov["Item", "Df"])
# much simpler is
quasiFsim.fnc(quasif)$quasiF
``` |

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