anova_tables | R Documentation |

Get ANOVA F-Table, contrasts, and pairwise comparisons

```
anova_tables(
x,
eta_squared = TRUE,
omega_squared = TRUE,
epsilon_squared = FALSE,
effects = "fixed",
contrast = NULL,
at = NULL,
standardized = TRUE,
unstandardized = TRUE,
ci = 0.95,
ci_method = NULL,
p_adjust = "none",
bootstrap = FALSE,
iterations = NULL,
pbkrtest.limit = NULL,
lmerTest.limit = NULL,
digits = 3,
id_col = "Subject",
print = TRUE
)
```

`x` |
an lmer model object |

`eta_squared` |
logical. Include partial-eta sqaured effect size? Default: TRUE |

`omega_squared` |
logical. Include omega sqaured effect size? Default: TRUE |

`epsilon_squared` |
logical. Include epsilon sqaured effect size? Default: FALSE |

`effects` |
"fixed" or "all". default is "fixed" to reduce computation time |

`contrast` |
The factor(s) at which to compare levels at |

`at` |
Additional interacting factor(s) to compare the effect of contrast at |

`standardized` |
Logical, indicating whether or not to print standardized estimates. Standardized estimates are based on "refit" of the model on standardized data but it will not standardize categorical predictors. Defualt is TRUE. |

`unstandardized` |
Logical, indicating whether or not to print unstandardized estimates. Default is TRUE. |

`ci` |
Confidence Interval (CI) level. Default to 0.95 |

`ci_method` |
Documention based on ?parameters::parameters. Method for computing degrees of freedom for confidence intervals (CI) and the related p-values. Allowed are following options (which vary depending on the model class): "residual", "normal", "likelihood", "satterthwaite", "kenward", "wald", "profile", "boot", "uniroot", "ml1", "betwithin", "hdi", "quantile", "ci", "eti", "si", "bci", or "bcai". See section Confidence intervals and approximation of degrees of freedom in model_parameters() for further details. When ci_method=NULL, in most cases "wald" is used then. |

`p_adjust` |
The p-values adjustment method for frequentist multiple comparisons. Can be one of "holm", "tukey", "hochberg", "hommel", "bonferroni", "BH", "BY", "fdr" or "none" (default). See the p-value adjustment section in the emmeans::test documentation. |

`bootstrap` |
Documention based on ?parameters::parameters. Should estimates be based on bootstrapped model? If TRUE, then arguments of Bayesian regressions apply (see also bootstrap_parameters()). |

`iterations` |
Documention based on ?parameters::parameters. The number of bootstrap replicates. This only apply in the case of bootstrapped frequentist models. |

`pbkrtest.limit` |
Optional parameter that can be set to help calculate dfs. If you need to use this a warning message will appear in the console telling you what to set this at. |

`lmerTest.limit` |
Optional parameter that can be set to help calculate dfs. If you need to use this a warning message will appear in the console telling you what to set this at. |

`digits` |
How many decimal places to round to? Default is 3. |

`id_col` |
The column containing subject ids. Default is "Subject" |

`print` |
Create a knitr table for displaying as html table? (default = TRUE) |

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