This function creates a user-specified number of simulated datasets, and compares mixed-effects models with quasi-F and F1 and F2 analyses. It should be run with the version of R and the version of languageR used by Baayen, Davidson & Bates (2008, JML), as mcmcsamp no longer supports models with random correlation parameters.

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`dat` |
Data frame with a data set with as variables Subject, Item and
SOA, as in the |

`with` |
Logical, if TRUE, an effect of SOA is built into the simulation. |

`nruns` |
Integer for the number of simulation runs. |

`nsub` |
Integer denoting the number of subjects. |

`nitem` |
Integer denoting the number of items. |

`...` |
other parameters to be passed through to plotting functions. |

Model parameters are estimated from the input data set.

For each completed simulation run, a dot is added to the R console.

A list with components

`alpha05` |
Description of 'comp1' |

`alpha01` |
proportion of runs in which predictors are significant at the 05 significance level. |

`res` |
Data frame with simulation results. |

`with` |
Logical, TRUE if SOA effect is built into the simulations. |

R. H. Baayen

See also `subjects.quasif.fnc`

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