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The goal of {cocoon}
is to provide functions that
flexibly format statistical output in a way that can be inserted into R
Markdown or Quarto documents. This is analogous to the apa_print()
functions in the {papaja}
package,
but functions in {cocoon}
can print Markdown or LaTeX
syntax. If your output document is a PDF, this doesn’t matter. But if
your output document is a Word document (as required by many journal
publishers), Markdown syntax generates editable output instead of an
image of output. The default style for statistical output follows American Psychological Association
style, but many defaults can be over-ridden to flexibly format
output.
You can install the development version of {cocoon}
from
GitHub with:
# install.packages("remotes")
::install_github("JeffreyRStevens/cocoon") remotes
For an example, we’ll create a correlation from the
mtcars
data set.
library(cocoon)
<- cor.test(mtcars$mpg, mtcars$disp))
(cars_corr #>
#> Pearson's product-moment correlation
#>
#> data: mtcars$mpg and mtcars$disp
#> t = -8.7472, df = 30, p-value = 9.38e-10
#> alternative hypothesis: true correlation is not equal to 0
#> 95 percent confidence interval:
#> -0.9233594 -0.7081376
#> sample estimates:
#> cor
#> -0.8475514
Now we can apply the format_stats()
function to
cars_corr
to create a Markdown-formatted character string
for the statistical results. We can embed this as inline R Markdown code
to generate the results.
Fuel efficiency and engine displacement were highly correlated (`r format_stats(cars_corr)`).
Fuel efficiency and engine displacement were highly correlated (r = -.85, 95% CI [-0.92, -0.71], p < .001).
We can also alter the output to allow other formatting. For instance, we may not like APA’s silly rule to remove leading zeros before a value that cannot exceed 1 (like correlations and p-values). And we may not want to include the confidence limits around the correlation coefficient. Finally, maybe we don’t want the statistics labels to be italicized.
Fuel efficiency and engine displacement were highly correlated (`r format_stats(cars_corr, pzero = TRUE, full = FALSE, italics = FALSE)`).
Fuel efficiency and engine displacement were highly correlated (r = -0.85, p < 0.001).
format_stats()
: Statistical objects
cor.test()
and
correlation::correlation()
, including Pearson’s, Kendall’s,
and Spearman’s correlations)t.test()
and wilcox.test()
, including
one-sample, two-sample independent, and paired tests){BayesFactor}
package)format_summary()
: Means and error (calculates from
vector or uses vector of mean and error interval or mean, lower error
limit, and upper error limit)format_p()
: P-valuesformat_bf()
: Bayes factors (numerics)format_scientific()
: Scientific notationformat_num()
: Other numbersformat_chr()
: Italicize character strings{papaja}
-
This package uses the apa_print()
function to convert a
number of R statistical objects into R Markdown output. However, it only
outputs LaTeX syntax and only generates APA formatted output with
minimal flexibility to alter the output.{apa}
-
This package also converts some R statistical objects to R Markdown
output. While it allows other output format such as Markdown, it also
only generates APA formatted output with minimal flexibility to alter
the output.{insight}
-
This package extracts information from model objects. It includes
format_p()
and format_bf()
functions that
achieves similar goals as in this package, but they do not allow as much
control over formatting of the labels or values.To cite {cocoon}
, use:
Stevens, Jeffrey R. (2024). cocoon: Extract, format, and print statistical output. (version 0.1.0) https://github.com/JeffreyRStevens/cocoon
Contributions
to {cocoon}
are most welcome! Feel free to check out open issues
for ideas. And pull requests
are encouraged, but you may want to raise
an issue or
contact the maintainer
first.
Please note that the cocoon project is released with a Contributor Code of Conduct. By contributing to this project, you agree to abide by its terms.
The package name {cocoon}
captures the main goal of
transforming statistical inputs into nicely formatted outputs. This
mirrors cocoons, which caterpillars build to transform into beautiful
adult insects. Cocoons
are formally defined as a case that the larvae of moths spin around
their pupa. So cocoons are cases built by moths and some other insects,
whereas butterflies produce a chrysalis, which forms from their
skin.
Photo source: Silk moths from Wikimedia Commons
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.