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tidystats

Author: Willem Sleegers License: MIT

tidystats is an R package for sharing and reporting statistics. tidystats extracts statistics from the output of statistical functions (e.g., t.test(), lm()) and stores them in a structured format. The resulting file can be shared with others and used in popular text editors to reproducibly report the statistics.

Please see below for instructions on how to install and use this package. If you find any bugs or have any feedback, please let me know by creating an issue here on Github.

Installation

tidystats can be installed from CRAN.

install.packages("tidystats")

You can also install the development version from GitHub using the remotes package.

remotes::install_github("willemsleegers/tidystats")

Usage

The main function is add_stats(). The function has 2 necessary arguments:

  • list: A list you want to add the statistics to.
  • output: The output of a statistics function (e.g., the output of t.test() or lm())

You also need an identifier to uniquely identify the output of a statistics function. You can provide an identifier (e.g., ‘weight_height_correlation’) with the identifier argument. If you do not provide an identifer, one is automatically created for you.

Optionally, you can also specify some additional meta-information:

  • type: A type that specifies the analysis as primary, secondary, or exploratory.
  • preregistered: Whether the analysis was preregistered or not.
  • notes: Additional information you think is useful to record.

Once all statistics are added to the list, you can write the contents to a file using the write_stats() function.

Example

The following example shows how to combine and save the statistics from three different statistical tests.

# Conduct a t-test, regression, and an ANOVA
sleep_test <- t.test(
  sleep$extra[sleep$group == 1],
  sleep$extra[sleep$group == 2],
  paired = TRUE
)

ctl <- c(4.17, 5.58, 5.18, 6.11, 4.50, 4.61, 5.17, 4.53, 5.33, 5.14)
trt <- c(4.81, 4.17, 4.41, 3.59, 5.87, 3.83, 6.03, 4.89, 4.32, 4.69)
group <- gl(2, 10, 20, labels = c("Ctl", "Trt"))
weight <- c(ctl, trt)
lm_D9 <- lm(weight ~ group)

npk_aov <- aov(yield ~ block + N * P * K, npk)

# Create an empty list to add the statistics to
statistics <- list()

# Add the statistics and specify some meta-information
statistics <- statistics |>
  add_stats(sleep_test, type = "primary") |>
  add_stats(lm_D9, preregistered = TRUE) |>
  add_stats(npk_aov, notes = "An ANOVA example")

# Save the statistics to a file
write_stats(statistics, "statistics.json")

The result is a .json file that contains all the statistics from the three statistical tests. If you want to see what this file looks like, you can inspect it here.

For a fully worked out example, see vignette("introduction-to-tidystats").

Supported statistical functions

tidystats supports functions from several statistics-related packages, including stats, lme4, BayesFactor, emmeans, and others. For a full list of supported packages and their functions, see vignette("supported-functions").

In some cases you need provide a class to the add_stats() function in order for tidystats to correctly extract the statistics. You can see a list of functions that require the class argument in the documentation of the add_stats() function (?add_stats).

If you want to use tidystats on an unsupported function, there are two things you can do:

  1. Request support for the new function by creating an issue.
  2. Manually extract the statistics and add them via add_stats() using the custom_stats() function. See the vignette("custom-statistics") for more information.

Reporting statistics

The file created with the write_stats() function can be used in the tidystats Microsoft Word add-in to report statistics in a Microsoft Word document. For more information, see the Word add-in page on the tidystats website.

More information

If you have any questions or comments, please create an issue here on GitHub.