Survapp: A Shiny Application for Survival Data Analysis

Abstract

There is a substantial demand for user-friendly graphical interfaces that empower professionals with limited programming knowledge to perform statistical analysis. Although R software is widely used for statistical analysis, it lacks an adequately intuitive graphical interface for individuals without statistical and programming skills. This paper aims to address this gap by introducing an application called Survapp, enabling users, regardless of their computational knowledge, to conduct survival analysis. The development leveraged R software, RStudio, and the Shiny package to create an interactive web app. Survapp incorporates diverse methodologies for analyzing survival data, including Kaplan-Meier, log-rank tests, Cox regression models, parametric accelerated failure time models, decision trees, random forests, and competitive risk analysis (a specific case of multi-state models). Survapp enables users to analyze survival data, offering example databases for various methodologies within the application. However, the primary objective is to allow users to import their own data and conduct their respective analyses in a user-friendly environment. A distinguishing aspect of Survapp is its interface, bridging the gap between complex statistical methods and users with limited statistical and programming expertise. Overall, Survapp proves to be a highly valuable tool for survival data analysis, catering to users needs and providing a user-friendly interface with a wide range of survival analysis methods. The Shiny app is available at the Shiny Apps repository: https://emanuel-vieira.shinyapps.io/survapp. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.