Glance version of the lm object into a flextable object — tabularise

Create a rich-formatted table with the 'glance' information from an lm object.

Usage

# S3 method for lm
tabularise_glance(
  data,
  header = TRUE,
  title = NULL,
  equation = TRUE,
  auto.labs = TRUE,
  origdata = NULL,
  labs = NULL,
  lang = getOption("data.io_lang", "en"),
  ...,
  kind = "ft",
  env = parent.frame()
)

Arguments

data: An lm 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).
equation: If TRUE (by default), add a equation to the table header. The equation can also be passed in the form of a character string (LaTeX).
auto.labs: If TRUE (by default), use labels (and units) automatically from data or origdata=.
origdata: The original data set this model was fitted to. By default it is NULL and no label is used (only the name of the variables).
labs: Labels to change the names of elements 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 can be set with, e.g., options(data.io_lang = "fr") for French.
...: Additional arguments passed to tabularise::equation()
kind: The kind of table to produce: "tt" for tinytable, or "ft" for flextable (default).
env: The environment where to evaluate lazyeval expressions (unused for now).

Value

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

Examples

iris_lm <- lm(data = iris, Petal.Length ~ Sepal.Length)
tabularise::tabularise$glance(iris_lm)
Linear model
NA
R2 Adj.R2 RSE t value p value Model df Log-likelihood AIC BIC Deviance Residuals df N
0.76 0.758 0.868 469 1.04·10-47 1 -191 387 396 111 148 150

Linear model
NA
R2	Adj.R2	RSE	t value	p value	Model df	Log-likelihood	AIC	BIC	Deviance	Residuals df	N
0.76	0.758	0.868	469	1.04·10-47	1	-191	387	396	111	148	150