Introducing {gtreg}: an R package to produce regulatory tables for clinical research

R in Pharma 2022 Workshop

πŸ—“ November 2, 2022 | 9:00am - 12:00pm EDT

🏨 Virtual

πŸ’₯ FREE workshop registration

Overview

In this workshop you will learn how to make standard regulatory tables and table shells for clinical research using the {gtreg} package in R. This includes: adverse event tables, summary tables with multi-line statistics for continuous variables, and raw data listings tables with grouped data. Table elements like headers, footers, or captions are customizable using {gtreg} column selectors, and the {gt} package can be used to implement final styling tweaks on your table. Lastly, {gtreg} tables are easily output to various formats, including HTML, PDF, RTF, Word, and Excel.

Learning objectives

Build and customize tables often required for clinical reporting.

Is this course for me?

If your answer to any of the following questions is β€œyes”, then this is the right workshop for you.

  • Do you make adverse event tables or descriptive statistics tables in R? Or table shells for either?

  • 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 assumed that participants 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 gtreg and other packages used in workshop.

    instll_pkgs <- c("gtreg", "gtsummary", "tidyverse", "labelled", "usethis")
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.

Instructors

Headshot of Shannon Pileggi

Shannon Pileggi (she/her) is a Lead Data Scientist at The Prostate Cancer Clinical Trials Consortium, a frequent blogger, and a member of the R-Ladies Global team. She enjoys automating data wrangling and data outputs, and making both data insights and learning new material digestible.



Headshot of Daniel D. Sjoberg

Daniel D. Sjoberg (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, R-Universe, GitHub, and internally at MSKCC. Daniel is the the winner of the 2021 American Statistical Association (ASA) Innovation in Statistical Programming and Analytics award.