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modelsummary creates tables and plots to present descriptive statistics and to summarize statistical models in R.

modelsummary is a package to summarize data and statistical models in R. It supports over one hundred types of models out-of-the-box, and allows users to report the results of those models side-by-side in a table, or in coefficient plots. It makes it easy to execute common tasks such as computing robust standard errors, adding significance stars, and manipulating coefficient and model labels. Beyond model summaries, the package also includes a suite of tools to produce highly flexible data summary tables, such as dataset overviews, correlation matrices, (multi-level) cross-tabulations, and balance tables (also known as “Table 1”). The appearance of the tables produced by modelsummary can be customized using external packages such as kableExtra, gt, flextable, or huxtable; the plots can be customized using ggplot2. Tables can be exported to many output formats, including HTML, LaTeX, Text/Markdown, Microsoft Word, Powerpoint, Excel, RTF, PDF, and image files. Tables and plots can be embedded seamlessly in rmarkdown, knitr, or Sweave dynamic documents. The modelsummary package is designed to be simple, robust, modular, and extensible (Arel-Bundock, 2022).

What?

modelsummary includes two families of functions:

  1. Model Summary
    • modelsummary: Regression tables with side-by-side models.
    • modelplot: Coefficient plots.
  2. Data Summary
    • datasummary: Powerful tool to create (multi-level) cross-tabs and data summaries.
    • datasummary_crosstab: Cross-tabulations.
    • datasummary_balance: Balance tables with subgroup statistics and difference in means (aka “Table 1”).
    • datasummary_correlation: Correlation tables.
    • datasummary_skim: Quick overview (“skim”) of a dataset.
    • datasummary_df: Turn dataframes into nice tables with titles, notes, etc.

Why?

Here are a few benefits of modelsummary over some alternative packages:

Easy

modelsummary is very easy to use. This simple call often suffices:

library(modelsummary)

mod <- lm(y ~ x, dat)

The command above will automatically display a summary table in the Rstudio Viewer or in a web browser. All you need is one word to change the output format. For example, a text-only version of the table can be printed to the Console by typing:

modelsummary(mod, output = "markdown")

Tables in Microsoft Word and LaTeX formats can be saved to file by typing:

modelsummary(mod, output = "table.docx")
modelsummary(mod, output = "table.tex")

Flexible

Information: The package offers many intuitive and powerful utilities to customize the information reported in a summary table. You can rename, reorder, subset or omit parameter estimates; choose the set of goodness-of-fit statistics to include; display various “robust” standard errors or confidence intervals; add titles, footnotes, or source notes; insert stars or custom characters to indicate levels of statistical significance; or add rows with supplemental information about your models.

Appearance: Thanks to the tinytable, gt, kableExtra, huxtable, flextable, and DT packages, the appearance of modelsummary tables is endlessly customizable. The appearance customization page shows tables with colored cells, weird text, spanning column labels, row groups, titles, source notes, footnotes, significance stars, and more. This only scratches the surface of possibilities.

Supported models: Thanks to the broom and parameters, modelsummary supports hundreds of statistical models out-of-the-box. Installing other packages can extend the capabilities further (e.g., broom.mixed). It is also very easy to add or customize your own models.

Output formats: modelsummary tables can be saved to HTML, LaTeX, Text/Markdown, Microsoft Word, Powerpoint, RTF, JPG, or PNG formats. They can also be inserted seamlessly in Rmarkdown documents to produce automated documents and reports in PDF, HTML, RTF, or Microsoft Word formats.

Dangerous

modelsummary is dangerous! It allows users to do stupid stuff like inserting squirrels in all your tables.

Reliable

modelsummary is reliably dangerous! The package is developed using a suite of unit tests with about 95% coverage, so it (probably) won’t break.

Community

modelsummary does not try to do everything. Instead, it leverages the incredible work of the R community. By building on top of the broom and parameters packages, modelsummary already supports hundreds of model types out-of-the-box. modelsummary also supports five of the most popular table-building and customization packages: gt, kableExtra, huxtable, flextable, and DT packages. By using those packages, modelsummary allows users to produce beautiful, endlessly customizable tables in a wide variety of formats, including HTML, PDF, LaTeX, Markdown, and MS Word.

One benefit of this community-focused approach is that when external packages improve, modelsummary improves as well. Another benefit is that leveraging external packages allows modelsummary to have a massively simplified codebase (relative to other similar packages). This should improve long term code maintainability, and allow contributors to participate through GitHub.

How?

You can install modelsummary from CRAN:

install.packages('modelsummary')

You can install the development version of modelsummary and its dependencies from R-Universe:

install.packages(
    c("modelsummary", "tinytable", "insight", "performance", "parameters"),
    repos = c(
        "https://vincentarelbundock.r-universe.dev",
        "https://easystats.r-universe.dev"))

Restart R completely before moving on.

Get started

The GET STARTED vignette will walk you through the basics of modelsummary.

You will find that there are a million ways to customize the tables and plots produced by modelsummary, but the Get Started page only scratches the surface. For details, see the vignettes:

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Version

Install

install.packages('modelsummary')

Monthly Downloads

22,164

Version

2.3.0

License

GPL-3

Maintainer

Vincent Arel-Bundock

Last Published

February 2nd, 2025

Functions in modelsummary (2.3.0)

NPercent

datasummary statistic shortcut
P0

datasummary statistic shortcut
N

datasummary statistic shortcut
Ncol

datasummary statistic shortcut
P75

datasummary statistic shortcut
Multicolumn

Use a variable as a factor to give rows in a table.
Var

datasummary statistic shortcut
SD

datasummary statistic shortcut
Percent

Pseudo-function to compute a statistic relative to a reference set.
Paste

Generate terms to paste values together in table.
PlusMinus

Generate 'x +/- y' terms in table.
config_modelsummary

Persistent user settings for the modelsummary package
datasummary_balance

Balance table: Summary statistics for different subsets of the data (e.g., control and treatment groups)
datasummary

Summary tables using 2-sided formulae: crosstabs, frequencies, table 1s and more.
datasummary_correlation

Generate a correlation table for all numeric variables in your dataset.
Min

datasummary statistic shortcut
RowFactor

Use a variable as a factor to give rows in a table.
PercentMissing

datasummary statistic shortcut
Median

datasummary statistic shortcut
RowNum

Display all observations in a table.
datasummary_skim

Quick overview of numeric or categorical variables
datasummary_df

Draw a table from a data.frame
coef_rename

Rename model terms
fmt_decimal

Rounding with decimal digits in the fmt argument
dvnames

Title models with their dependent variables
datasummary_correlation_format

Format the content of a correlation table
datasummary_crosstab

Cross tabulations for categorical variables
colLabels

Retrieve or modify the row or column labels.
fmt_significant

Rounding with significant digits in the fmt argument
fmt_equivalence

Rounding with number of digits determined by an equivalence test
fmt_sci

Rounding using scientific notation
do_call

safe do.call
fmt_term

Rounding with decimal digits on a per-term basis in the fmt argument for modelsummary()
dsummary

dsummary() is a shortcut to datasummary()
get_estimates

Extract model estimates in a tidy format.
get_vcov.mlm

Allow users to override uncertainty estimates
escape_string

Make sure LaTeX and HTML are safe to compile
escape_latex

Escape problematic characters to allow compilation in LaTeX
glance_custom

Extract custom information from a model object and turn it into a tidy data.frame or tibble with a single row.
escape_html

Escape problematic characters to allow display in HTML
fmt_statistic

Rounding with decimal digits on a per-statistic basis in the fmt argument for modelsummary()
fmt_sprintf

Rounding with the sprintf() function in the fmt argument
get_vcov

Allow users to override uncertainty estimates
get_gof_parameters

Extract goodness-of-fit statistics from a single model using the performance package
map_estimates

rename and reorder estimates from a single model (before merging to collapse)
hush

Execute code silently
modelsummary

Model Summary Tables
modelplot

Model Summary Plots with Estimates and Confidence Intervals
get_gof

Extract goodness-of-fit statistics a tidy format.
get_gof_broom

Extract goodness-of-fit statistics from a single model using the broom package or another package with package which supplies a method for the generics::glance generic.
labelSubset

Add a label to a logical vector.
glance_custom_internal.lm

Avoid namespace conflict when we want to customize glance internally and still allow users to do the same with their own functions
gof_map

Data.frame used to clean up and format goodness-of-fit statistics
tidy_custom

Extract custom information from a model object and turn it into a tidy data.frame or tibble
tidy_custom_internal.default

Avoid namespace conflict when we want to customize glance internally and still allow users to do the same with their own functions
glance_custom_internal.default

Avoid namespace conflict when we want to customize glance internally and still allow users to do the same with their own functions
map_gof

Internal function to subset, rename and re-order gof statistics
glance_custom_internal

Avoid namespace conflict when we want to customize glance internally and still allow users to do the same with their own functions
reexports

tidy generic
tidy_custom_internal

Avoid namespace conflict when we want to customize glance internally and still allow users to do the same with their own functions
msummary

msummary() is a shortcut to modelsummary()
update_modelsummary

Update modelsummary and its dependencies
rowLabels

Retrieve or modify the row or column labels.
supported_models

List of model objects from which modelsummary can extract estimates and statistics
Mean

datasummary statistic shortcut
Heading

'Heading' pseudo-function
Arguments

'Arguments' pseudo-function
NUnique

datasummary statistic shortcut
Max

datasummary statistic shortcut
DropEmpty

'DropEmpty' pseudo-function
Factor

Use a variable as a factor to give rows in a table.
Histogram

datasummary statistic shortcut
Format

Use a variable as a factor to give rows in a table.
AllObs

Display all observations in a table.
All

Include all columns of a dataframe.
P25

datasummary statistic shortcut
P100

datasummary statistic shortcut
P50

datasummary statistic shortcut