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

# S3 method for class 'summary.nls'
tabularise_coef(
  data,
  header = TRUE,
  title = header,
  equation = header,
  auto.labs = TRUE,
  origdata = NULL,
  labs = NULL,
  lang = getOption("SciViews_lang", "en"),
  footer = FALSE,
  show.signif.stars = getOption("show.signif.stars", TRUE),
  ...,
  kind = "ft"
)

Arguments

data

An 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).

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 language to use. The default value can be set with, e.g., options(SciViews_lang = "fr") for French.

If FALSE (by default), add a footer to the table.

show.signif.stars

If TRUE, add the significance stars to the table. The default is getOption("show.signif.stars")

...

Not used

kind

The kind of table to produce: "tt" for tinytable, or "ft" for flextable (default).

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)

Nonlinear least squares logistic model

weight=Asym1+e(xmidTime)/scal+ϵ\begin{aligned} \operatorname{weight} = \frac{Asym}{1 + e^{(xmid - \operatorname{Time}) /scal}} + \epsilon \end{aligned}

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

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