R/tabularise.nls.R
tabularise_tidy.nls.Rd
Extract the information contained in a nls object into a rectangular table as
it could be obtained by broom::tidy()
. Here, the table is nicely
formatted as an (almost) publication-ready form (good for informal reports,
notebooks, etc).
# S3 method for class 'nls'
tabularise_tidy(
data,
header = TRUE,
title = header,
equation = header,
auto.labs = TRUE,
origdata = NULL,
labs = NULL,
lang = getOption("SciViews_lang", "en"),
show.signif.stars = getOption("show.signif.stars", TRUE),
...,
kind = "ft"
)
An nls object.
If TRUE
(by default), add a title to the table.
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).
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).
If TRUE
(by default), use labels (and units) automatically
from data or 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).
Labels to change the names of elements in the term
column of
the table. By default it is NULL
and nothing is changed.
The language to use. The default value can be set with, e.g.,
options(SciViews_lang = "fr")
for French.
If TRUE
, add the significance stars to the table.
The default is getOption("show.signif.stars")
Not used
The kind of table to produce: "tt" for tinytable, or "ft" for flextable (default).
A flextable object that you can print in different forms or rearrange with the {flextable} functions.
data("ChickWeight", package = "datasets")
chick1 <- ChickWeight[ChickWeight$Chick == 1, ]
# Adjust a logistic curve
chick1_logis <- nls(data = chick1, weight ~ SSlogis(Time, Asym, xmid, scal))
tabularise::tabularise$tidy(chick1_logis)
Nonlinear least squares logistic model
Term
Estimate
Standard Error
tobs. value
p value
signif
Asym
937.0
465.868
2.01
7.52·10-02
.
xmid
35.2
8.312
4.24
2.18·10-03
**
scal
11.4
0.905
12.60
5.08·10-07
***
0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05
tabularise::tabularise$tidy(chick1_logis, lang = "fr")
Nonlinear least squares logistic model
Term
Estimate
Standard Error
tobs. value
p value
signif
Asym
937.0
465.868
2.01
7.52·10-02
.
xmid
35.2
8.312
4.24
2.18·10-03
**
scal
11.4
0.905
12.60
5.08·10-07
***
0 <= '***' < 0.001 < '**' < 0.01 < '*' < 0.05