tabularise_coef.summary.nls: Create a rich-formatted table using the table of coefficients...

In SciViews/modelit: Statistical Models for 'SciViews::R'

Create a rich-formatted table using the table of coefficients of the summary.nls object

Description

This function extracts and formats the table of coefficients from a summary.nls object, similar to stats::coef(), but in flextable object.

Usage

## S3 method for class 'summary.nls'
tabularise_coef(
  data,
  header = TRUE,
  title = NULL,
  equation = header,
  lang = getOption("data.io_lang", "en"),
  show.signif.stars = getOption("show.signif.stars", TRUE),
  ...,
  kind = "ft",
  env = parent.frame()
)

Arguments

data	A summary.nls object.
header	If TRUE (by default), add a title 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	Add equation of the model to the table. If TRUE, equation() is used. The equation can also be passed in the form of a character string (LaTeX equation).
lang	The language to use. The default value can be set with, e.g., options(data.io_lang = "fr") for French.
show.signif.stars	If TRUE (by default), add the significance stars to the table.
...	Additional arguments passed to 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 forms or rearrange with the {flextable} functions.

Examples

data("ChickWeight", package = "datasets")
chick1 <- ChickWeight[ChickWeight$Chick == 1, ]
# Adjust a logistic curve
chick1_logis <- nls(data = chick1, weight ~ SSlogis(Time, Asym, xmid, scal))
chick1_logis_sum <- summary(chick1_logis)

tabularise::tabularise$coef(chick1_logis_sum)
tabularise::tabularise$coef(chick1_logis_sum, header = FALSE, equation = TRUE)

SciViews/modelit documentation built on Nov. 24, 2024, 10:23 a.m.