Introduction to RShiny.

Building statistical tools that enable scientists without a background in statistics or computer science to perform simple statistical analysis in a accessible manner. R Shiny apps are also particularly useful when the output of analysis is large and complicated to to navigate in a markdown report. It enables to user to select directly the output of interest at any time and visioning it in a concise manner.

I have been trying to encourage my coworkers to embrace this idea when presenting statistical results to doctors as they usually have very little knowledge about R but love exploring every detail of an analysis. The syntax of Shiny can be a bit counter intuitive at first but it will grow on you as discover it’s many functionalities and marvel in your own progress!

I wrote a quick introduction to R Shiny and a full set of documents and code with a couple apps as examples.

Axel S. Martin
Axel S. Martin
Research Biostatistician

My research interests include high-dimensional time-to-event data prediction and stratification in cancer genomics, lately I have also developed an interest in causal inference and individualized treatment rules.