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Repeated measures model class

A `RepeatedMeasuresModel`

object represents
a model fitted to data with multiple measurements per subject. The
object comprises data, fitted coefficients, covariance parameters,
design matrix, error degrees of freedom, and between- and within-subjects
factor names for a repeated measures model. You can predict model
responses using the `predict`

method and generate
random data at new design points using the `random`

method.

You can fit a repeated measures model using `fitrm(t,modelspec)`

.

anova | Analysis of variance for between-subject effects |

epsilon | Epsilon adjustment for repeated measures anova |

grpstats | Compute descriptive statistics of repeated measures data by group |

manova | Multivariate analysis of variance |

margmean | Estimate marginal means |

mauchly | Mauchly's test for sphericity |

multcompare | Multiple comparison of estimated marginal means |

plot | Plot data with optional grouping |

plotprofile | Plot expected marginal means with optional grouping |

predict | Compute predicted values given predictor values |

random | Generate new random response values given predictor values |

ranova | Repeated measures analysis of variance |

Wilkinson notation describes the factors present in models. It does not describe the multipliers (coefficients) of those factors.

Use these rules to specify the responses in `modelspec`

.

Wilkinson Notation | Description |
---|---|

`Y1,Y2,Y3` | Specific list of variables |

`Y1-Y5` | All table variables from `Y1` through `Y5` |

Use these rules to specify terms in `modelspec`

.

Wilkinson Notation | Factors in Standard Notation |
---|---|

`1` | Constant (intercept) term |

`X^k` , where `k` is a positive
integer | `X` , `X` ,
..., `X` |

`X1 + X2` | `X1` , `X2` |

`X1*X2` | `X1` , `X2` , `X1*X2` |

`X1:X2` | `X1*X2` only |

`-X2` | Do not include `X2` |

`X1*X2 + X3` | `X1` , `X2` , `X3` , `X1*X2` |

`X1 + X2 + X3 + X1:X2` | `X1` , `X2` , `X3` , `X1*X2` |

`X1*X2*X3 - X1:X2:X3` | `X1` , `X2` , `X3` , `X1*X2` , `X1*X3` , `X2*X3` |

`X1*(X2 + X3)` | `X1` , `X2` , `X3` , `X1*X2` , `X1*X3` |

Statistics and Machine Learning Toolbox™ notation always includes a constant term
unless you explicitly remove the term using `-1`

.

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