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Create a rich-formatted table from the summary of a nls object

Source: R/tabularise.nls.R
tabularise_default.summary.nls.Rd

Create a table of a summary.nls object. This table looks like the output of print.summary.nls() but richly formatted. The tabularise_coef() function offers more customization options for this object.

Usage

# S3 method for summary.nls
tabularise_default(
  data,
  header = TRUE,
  title = NULL,
  equation = header,
  footer = TRUE,
  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 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

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).

footer

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

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 (Not used).

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.

See also

tabularise::tabularise(), tabularise::tabularise_tidy(), tabularise_coef.summary.nls()

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(chick1_logis_sum)

Nonlinear least squares  logistic model
NA
Term
Estimate
Standard Error
tobs. value
p value
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
Residual standard error : 2.919 on 9 degrees of freedom
Number of iterations to convergence : 0
Achieved convergence tolerance : 7.343e-06
tabularise::tabularise(chick1_logis_sum, footer = FALSE)

Nonlinear least squares  logistic model
NA
Term
Estimate
Standard Error
tobs. value
p value
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