pammtools: Survival Analysis using Generalized Additive Mixed Models

Abstract

In medical applications, time-to-event is often an important outcome, e.g., when investigating survival, remission, graft failure, and other outcomes. The Piece-wise exponential Additive Mixed Model (PAMM) is a powerful model class for survival analysis, based on Generalized Additive Mixed Models. It offers intuitive specification and robust estimation of complex survival models with stratified baseline hazards, frailty, time-varying effects, cumulative effects and competing risks. The R package pammtools provides a tidy workflow for survival analysis with PAMMs, including data simulation, transformation and other functions for data preprocessing and model post-processing as well as visualization. This talk briefly introduces the Piece-wise exponential Additive Mixed Model for survival analysis and illustrates its application using pammtools.