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tidysummary

The goal of tidysummary is to streamlines the analysis of clinical data by automatically selecting appropriate statistical descriptions and inference methods based on variable types. See the vignette for more details.

Installation

You can install the development version of tidysummary like so:

if (!requireNamespace("remotes", quietly = TRUE)) {
  install.packages("remotes")
}
remotes::install_github("htqqdd/tidysummary")

Usage

A quick example

library(tidysummary)
result <- iris %>%
  add_var() %>%
  add_summary() %>%
  add_p()

Another example

#Here is an prepared dataset
iris <- iris %>%
  mutate(group = factor(rep(1:3, each = 50),
                        labels = c("group1", "group2", "group3")))

#Now use tidysummary
library(tidysummary)
result <- iris %>%
  add_var() %>%
  add_summary(binary_show = "all") %>%
  add_p()

Following options

  • Use as DataFrame
View(result)
  • Display as HTML (use kableExtra or others your prefer)
library(kableExtra)
result[is.na(result)] <- ""
result %>%
  kbl(caption = "Table 1. Summary of Iris Dataset",
      row.names = F,
      align = "c") %>%
  kable_classic(full_width = FALSE, html_font = "Cambria")

  • Save as Excel (.xlsx)
result %>%
  writexl::write_xlsx("./test.xlsx")

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Version

Install

install.packages('tidysummary')

Version

0.1.0

License

MIT + file LICENSE

Maintainer

Xiang Li

Last Published

July 15th, 2025

Functions in tidysummary (0.1.0)

normal_test

Perform normality test on a variable
add_p

Add statistical test results to summary data
format_p

Format p-values with significance markers
equal_test

Test for Equality of Variances
add_summary

Add summary statistics to a add_var object
add_var

Prepare variables for add_summary
small_test

Check Sample Size Adequacy for Chi-Squared Test