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https://github.com/kaz-yos/tableone

R package to create "Table 1", description of baseline characteristics with or without propensity score weighting
https://github.com/kaz-yos/tableone

baseline-characteristics cran descriptive-statistics r statistics

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R package to create "Table 1", description of baseline characteristics with or without propensity score weighting

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README 

        
---

output: github_document

---



```{r, message = FALSE, tidy = FALSE, echo = F}

## knitr configuration: https://yihui.name/knitr/options#chunk_options

library(knitr)

showMessage <- FALSE

showWarning <- TRUE

set_alias(w = "fig.width", h = "fig.height", res = "results")

opts_chunk$set(comment = "##", error= TRUE, warning = showWarning, message = showMessage,

               tidy = FALSE, cache = FALSE, echo = TRUE,

               fig.width = 7, fig.height = 7,

               fig.path = "man/figures")

## for rgl

## knit_hooks$set(rgl = hook_rgl, webgl = hook_webgl)

## for animation

opts_knit$set(animation.fun = hook_ffmpeg_html)

## R configuration

options(width = 116, scipen = 5)

```



# tableone



[![R-CMD-check](https://github.com/kaz-yos/tableone/workflows/R-CMD-check/badge.svg)](https://github.com/kaz-yos/tableone/actions)

[![](https://www.r-pkg.org/badges/version/tableone)](https://www.r-pkg.org/pkg/tableone)

[![CRAN RStudio mirror downloads](https://cranlogs.r-pkg.org/badges/tableone)](https://www.r-pkg.org/pkg/tableone)



**An R package to create "Table 1", description of baseline characteristics**



Creates "Table 1", i.e., description of baseline patient characteristics, which is essential in every medical research. Supports both continuous and categorical variables, as well as p-values and standardized mean differences. Weighted data are supported via the survey package.



tableone was inspired by descriptive statistics functions in Deducer , a Java-based GUI package by Ian Fellows. This package does not require GUI or Java, and intended for command-line users.



# tableone in action



![screencast](man/figures/tableone.gif "screencast")



The code being executed can be found in the introduction vignette.



# tableone code example



In this table, continuous and categorical variables can be placed in any order. The p-valeus are from exact tests for pre-specified variables. For nonnormal variables, it shows median and IQR instead of mean and SD, and p-values are from nonparametric tests. Numerically coded categorical variables can be transformed on the fly with factorVars. SMD stands for standardized mean differences. For weighted data, first created a svydesign object, and use the svyCreateTableOne() function. Most other options remain the same.



```{r}

## Load package

library(tableone)

## Load data

data(pbc, package = "survival")

# drop ID from variable list

vars <- names(pbc)[-1]

## Create Table 1 stratified by trt (can add more stratifying variables)

tableOne <- CreateTableOne(vars = vars, strata = c("trt"), data = pbc,

                            factorVars = c("status","edema","stage"))

## Specifying nonnormal variables will show the variables appropriately,

## and show nonparametric test p-values. Specify variables in the exact

## argument to obtain the exact test p-values.

print(tableOne, nonnormal = c("bili","chol","copper","alk.phos","trig"),

      exact = c("status","stage"), smd = TRUE,

      formatOptions = list(big.mark = ","))

```



# Installation



This version of tableone package for R is developmetal, and may not be available from the CRAN. You can install it using one of the following way.



**Direct installation from github**



You first need to install the devtools package to do the following. You can choose from the latest stable version and the latest development version.



```{r, eval = FALSE}

## Install devtools (if you do not have it already)

install.packages("devtools")

## Install directly from github (develop branch)

devtools::install_github(repo = "kaz-yos/tableone", ref = "develop")

```



Using devtools may requires some preparation, please see the following link for information.



https://www.rstudio.com/projects/devtools/



# Contributors



I would like to thank all the contributors!



- Alexander Bartel [ndevln](https://github.com/ndevln)

- Jonathan J Chipman [chipmanj](https://github.com/chipmanj)

- Justin Bohn [jmb01](https://github.com/jmb01)

- Lucy D'Agostino McGowan [LucyMcGowan](https://github.com/LucyMcGowan)

- Malcolm Barrett [malcolmbarrett](https://github.com/malcolmbarrett)

- Rune Haubo B Christensen [runehaubo](https://github.com/runehaubo)

- [gbouzill](https://github.com/gbouzill)



# Similar or complementary projects



There are multiple similar or complementary projects of interest.



- DescTools: Tools for Descriptive Statistics. https://cran.r-project.org/web/packages/DescTools/index.html

- Gmisc: Descriptive Statistics, Transition Plots, and More. https://cran.r-project.org/web/packages/Gmisc/

- Hmisc (summary.formula): Advanced table making and many more. https://github.com/harrelfe/Hmisc/

- arsenal: An Arsenal of 'R' Functions for Large-Scale Statistical Summaries. https://github.com/eheinzen/arsenal

- atable: Create Tables for Reporting Clinical Trials. https://github.com/arminstroebel/atable

- compareGroups: Descriptive Analysis by Groups. http://www.comparegroups.eu

- expss: Tables with Labels and Some Useful Functions from Spreadsheets and 'SPSS' Statistics. https://github.com/gdemin/expss

- finalfit: Quickly Create Elegant Regression Results Tables and Plots when Modelling. https://finalfit.org/index.html

- framework for easily create tables for reporting: framework for easily create tables for reporting. https://davidgohel.github.io/flextable/

- furniture: Furniture for Quantitative Scientists. https://cran.r-project.org/web/packages/furniture/

- gtsummary: Presentation-Ready Data Summary and Analytic Result Tables.  https://CRAN.R-project.org/package=gtsummary

- htmlTable: An R package for generating advanced tables. https://github.com/gforge/htmlTable

- kableExtra: Construct Complex Table with 'kable' and Pipe Syntax. https://github.com/haozhu233/kableExtra

- pander: An R Pandoc Writer. https://rapporter.github.io/pander/

- pixiedust: Format models for console and to markdown, HTML, and LaTeX. https://github.com/nutterb/pixiedust

- qwraps2: quickly placing data summaries and formatted regression results into .Rnw or .Rmd files. https://github.com/dewittpe/qwraps2/

- stargazer: Well-Formatted Regression and Summary Statistics Tables. https://cran.r-project.org/web/packages/stargazer/index.html

- tab: Functions for Creating Summary Tables for Statistical Reports. https://cran.r-project.org/package=tab

- table1: Tables of Descriptive Statistics in HTML. https://github.com/benjaminrich/table1

- table1xls: Exports Reproducible Summary Tables to Multi-Tab Spreadsheet Files. https://cran.r-project.org/web/packages/table1xls/index.html

- xtable: Export Tables to LaTeX or HTML. https://cran.r-project.org/web/packages/xtable/index.html

- (Python) tableone: Create "Table 1" for research papers in Python. https://github.com/tompollard/tableone