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---
title: "Clinical Reporting with {gtsummary}"
subtitle: "R/Medicine 2022 Workshop"
editor: source
---
<!-- https://github.com/rstudio-conf-2022/teach-ds -->
------------------------------------------------------------------------
🗓️ August 23, 2022 \| 11:00am - 2:00pm EDT
🏨 Virtual
💥 **FREE** with [conference registration](https://events.linuxfoundation.org/r-medicine/register/) (\$10 to \$50)
📝 To register for the workshop, follow instructions in the email "*R/Medicine 2022 - How to Prepare*" you received after conference registration
------------------------------------------------------------------------
# Overview
The [**gtsummary**](https://www.danieldsjoberg.com/gtsummary/) package provides an elegant and flexible way to create publication-ready summary tables in **R**.
A critical part of the work of statisticians, data scientists, and analysts is summarizing data sets and regression models in R and publishing or sharing polished summary tables.
The [**gtsummary**](https://www.danieldsjoberg.com/gtsummary/) package was created to streamline these everyday analysis tasks by allowing users to easily create reproducible summaries of data sets, regression models, survey data, and survival data with a simple interface and very little code.
The package follows a tidy framework, making it easy to integrate with standard data workflows, and offers many table customization features through function arguments, helper functions, and custom themes.
## Learning objectives
Build, customize, and report tables often found in medical journals and other research-related publications.
## Is this course for me?
If your answer to any of the following questions is "yes", then this is the right workshop for you.
- Do you make summary tables in R (data, survey data, regression models, time-to-event data, adverse event reports)?
- Do you want your workflow to be reproducible?
- Are you often frustrated with the immense amount of code required to create great-looking tables in R?
The workshop is designed for those with some experience in R.
It will be expected that you can perform basic data manipulation.
Experience with the {tidyverse} and the `%>%` operator is a plus, but not required.
## Prework
Before attending the workshop please have the following installed and configured on your machine.
- Recent version of **R**
- Recent version of **RStudio**
- Most recent release of the [**gtsummary**](https://www.danieldsjoberg.com/gtsummary/) and other packages used in workshop.
```r
instll_pkgs <-
c("gtsummary", "tidyverse", "labelled", "usethis",
"causaldata", "fs", "skimr", "car", "emmeans")
install.packages(instll_pkgs)
```
- Ensure you can knit R markdown documents
- Open RStudio and create a new Rmarkdown document
- Save the document and check you are able to knit it.
# Instructor
{style="float:right;padding: 0 0 0 10px;" fig-alt="Headshot of Daniel D. Sjoberg" width="200"}
[**Daniel D. Sjoberg**](https://www.danieldsjoberg.com/) (he/him) is a Senior Biostatistician at Memorial Sloan Kettering Cancer Center in New York City and a DrPH candidate in Biostatistics at Columbia University. His research interests include adaptive methods in clinical trials, precision medicine, and predictive modeling. He also enjoys R package development, creating many packages available on [CRAN](https://cran.r-project.org/web/packages/), [R-Universe](https://ddsjoberg.r-universe.dev/ui#packages), [GitHub](https://github.com/ddsjoberg), and internally at MSKCC. Daniel is the winner of the 2021 American Statistical Association (ASA) Innovation in Statistical Programming and Analytics award.