# RepeatedMeasuresModel

Repeated measures model object

## Description

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.

## Creation

Fit a repeated measures model and create a `RepeatedMeasuresModel`

object using `fitrm`

.

## Properties

## Object Functions

`ranova` | Repeated measures analysis of variance |

`anova` | Analysis of variance for between-subject effects in a repeated measures model |

`mauchly` | Mauchly’s test for sphericity |

`epsilon` | Epsilon adjustment for repeated measures anova |

`multcompare` | Multiple comparison of estimated marginal means |

`manova` | Multivariate analysis of variance |

`coeftest` | Linear hypothesis test on coefficients of repeated measures model |

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

`margmean` | Estimate 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 |

## Examples

## More About

## Version History

**Introduced in R2014a**