Create a rich-formatted table from an anova object

Usage

# S3 method for anova
tabularise_default(
  data,
  header = TRUE,
  title = header,
  auto.labs = TRUE,
  origdata = NULL,
  labs = NULL,
  lang = getOption("data.io_lang", "en"),
  show.signif.stars = getOption("show.signif.stars", TRUE),
  ...,
  kind = "ft",
  env = parent.frame()
)

Arguments

data: An anova object
header: If TRUE (by default), add a header to the table
title: If TRUE, add a title to the table header. Default to the same value than header, except outside of a chunk where it is FALSE if a table caption is detected (tbl-cap YAML entry).
auto.labs: If TRUE (by default), use labels (and units) automatically (from origdata=)
origdata: The original data set used for the ANOVA. By default it is NULL. Used to extract labels that are lost in the anova object.
labs: Labels to change the default names in the term column of the table. By default it is NULL and nothing is changed.
lang: The natural language to use. The default value is set with, e.g., options(data.io_lang = "fr") for French.
show.signif.stars: If TRUE, add the significance stars to the table. The default is taken from getOption("show.signif.stars").
...: Additional arguments (not used for now)
kind: The kind of table to produce: "tt" for tinytable, or "ft" for flextable (default).
env: The environment where to evaluate lazyeval expressions (not used for now)

Value

A flextable object you can print in different form or rearrange with the {flextable} functions.

Examples

iris_anova <- anova(lm(data = iris, Petal.Length ~ Species))
tabularise::tabularise(iris_anova)
Analysis of variance
Response: Petal.Length
Term Df Sum of squares Mean squares Fobs. value p value 
Species 2 437.1 218.551 1180 < 2·10-16 ***
Residuals 147  27.2   0.185 
0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05

Analysis of variance Response: Petal.Length
Term	Df	Sum of squares	Mean squares	Fobs. value	p value
Species	2	437.1	218.551	1180	< 2·10-16	***
Residuals	147	27.2	0.185
0 <= '*' < 0.001 < '' < 0.01 < '*' < 0.05