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https://github.com/vincentarelbundock/modelsummary

Beautiful and customizable model summaries in R.
https://github.com/vincentarelbundock/modelsummary

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Beautiful and customizable model summaries in R.

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README 

        









 
 















`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)](https://doi.org/10.18637/jss.v103.i01).



## 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](#alternative-packages):



#### Easy



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



``` r

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:



``` r

modelsummary(mod, output = "markdown")

```



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

typing:



``` r

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

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

```



#### Flexible



*Information*: The package offers many intuitive and powerful utilities

to [customize the

information](https://modelsummary.com/articles/modelsummary.html)

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`](https://vincentarelbundock.github.io/tinytable/),

[`gt`](https://gt.rstudio.com),

[`kableExtra`](https://haozhu233.github.io/kableExtra/),

[`huxtable`](https://hughjonesd.github.io/huxtable/),

[`flextable`](https://davidgohel.github.io/flextable/), and

[`DT`](https://rstudio.github.io/DT/) packages, the appearance of

`modelsummary` tables is endlessly customizable. The [appearance

customization page](https://modelsummary.com/articles/appearance.html)

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`](https://broom.tidymodels.org/) and

[`parameters`](https://easystats.github.io/parameters/), `modelsummary`

supports *hundreds* of statistical models out-of-the-box. Installing

other packages can extend the capabilities further (e.g.,

[`broom.mixed`](https://CRAN.R-project.org/package=broom.mixed)). It is

also very easy to [add or customize your own

models.](https://modelsummary.com/articles/modelsummary.html#adding-new-models-1)



*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.](https://modelsummary.com/articles/modelsummary.html#rmarkdown-and-knitr-1)



#### Dangerous



`modelsummary` is dangerous! It allows users to do stupid stuff like

[inserting squirrels in all your

tables.](https://modelsummary.com/articles/appearance.html#gt-1)






#### Reliable



`modelsummary` is *reliably* dangerous! The package is developed using a

[suite of unit

tests](https://github.com/vincentarelbundock/modelsummary/tree/main/inst/tinytest)

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:



``` r

install.packages('modelsummary')

```



You can install the development version of `modelsummary` and its

dependencies from R-Universe:



``` r

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](https://modelsummary.com/vignettes/get_started.html)

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](https://modelsummary.com/vignettes/get_started.html) only

scratches the surface. For details, see the vignettes:



-   [Data

    Summaries](https://modelsummary.com/vignettes/datasummary.html)

-   [Model

    Summaries](https://modelsummary.com/vignettes/modelsummary.html)

-   [Model Plots](https://modelsummary.com/vignettes/modelplot.html)

-   [`modelsummary` extensions and

    customization](https://modelsummary.com/vignettes/modelsummary_extension.html)

-   [Themes and

    Styles](https://modelsummary.com/vignettes/appearance.html)