Tidy version of the anova object into a flextable object

# S3 method for class 'anova'
tabularise_tidy(data, ...)

Arguments

data: An anova object
...: Additional arguments used tabularise_default.anova()

Value

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

Examples

is <- data.io::read("iris", package = "datasets")

is_lm1 <- lm(data = is, petal_length ~ species)

library(tabularise)

anova(is_lm1) |> tabularise_tidy()
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
# identical
anova(is_lm1) |> tabularise$tidy()
Analysis of variance
Response: petal_length
Term Df Sum of squares Mean squares Fobs. value p value 
species 2 437.1 218.551 1180 < 2·10-16 ***
Residuals 147  27.2   0.185 
0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05
# Use labels
anova(is_lm1) |> tabularise$tidy(origdata = is)
Analysis of variance
Response: Length of the petals  [cm]
Term Df Sum of squares Mean squares Fobs. value p value 
Iris species 2 437.1 218.551 1180 < 2·10-16 ***
Residuals 147  27.2   0.185 
0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05

# alternative with anova_() in {modelit} package
anova_(is_lm1) |> tabularise$tidy()
Analysis of variance
Response: Length of the petals  [cm]
Term Df Sum of squares Mean squares Fobs. value p value 
Iris 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