## Repeated Measures ANOVA

### Example usage

### Arguments

data | the data as a data frame |

rm | a list of lists, where each list describes the label (as a string) and the levels (as vector of strings) of a particular repeated measures factor |

rmCells | a list of lists, where each list decribes a repeated measure (as a string) from data defined as measure and the particular combination of levels from rm that it belongs to (as a vector of strings) defined as cell |

bs | a vector of strings naming the between subjects factors from data |

cov | a vector of strings naming the covariates from data. Variables must be numeric |

rmTerms | a list of character vectors describing the repeated measures terms to go into the model |

bsTerms | a list of character vectors describing the between subjects terms to go into the model |

ss | '2' or '3' (default), the sum of squares to use |

effectSize | one or more of 'eta', 'partEta', or 'omega'; use η², partial η², and ω² effect sizes, respectively |

spherTests | TRUE or FALSE (default), perform sphericity tests |

spherCorr | one or more of 'none' (default), 'GG', or HF; use no p-value correction, the Greenhouse-Geisser p-value correction, and the Huynh-Feldt p-value correction for shericity, respectively |

leveneTest | TRUE or FALSE (default), test for equality of variances (i.e., Levene's test) |

contrasts | in development |

postHoc | a list of character vectors describing the post-hoc tests that need to be computed |

postHocCorr | one or more of 'none', 'tukey' (default), 'scheffe', 'bonf', or 'holm'; use no, Tukey, Scheffe, Bonferroni and Holm posthoc corrections, respectively |

descStats | TRUE or FALSE (default), provide descriptive statistics |

emMeans | a list of lists specifying the variables for which the estimated marginal means need to be calculate. Supports up to three variables per term. |

ciEmm | TRUE (default) or FALSE, provide a confidence interval for the estimated marginal means |

ciWidthEmm | a number between 50 and 99.9 (default: 95) specifying the confidence interval width for the estimated marginal means |

emmPlots | TRUE (default) or FALSE, provide estimated marginal means plots |

emmTables | TRUE or FALSE (default), provide estimated marginal means tables |

emmWeights | TRUE (default) or FALSE, weigh each cell equally or weigh them according to the cell frequency |

### Returns

A results object containing:

results$rmTable | a table |

results$bsTable | a table |

results$assump$spherTable | a table |

results$assump$leveneTable | a table |

results$contrasts | an array of tables |

results$postHoc | an array of tables |

results$emm | an array of groups |

Tables can be converted to data frames with asDF or as.data.frame(). For example:

results$rmTable$asDF

as.data.frame(results$rmTable)

Elements in arrays can be accessed with [[n]]. For example:

results$contrasts[[1]] # accesses the first element