Resources for Survival Analysis

Extended Joint Models for Longitudinal and Survival Data

Competing Risks and Survival Analysis

Code repository for the manuscript 'Validation of the performance of competing risks prediction models: a guide through modern methods' (2023, BMJ)

Finite-Interval Forecasting Engine: Machine learning models for discrete-time survival analysis and multivariate time series forecasting

Targeted Learning for Survival Analysis

R package for fitting joint models to time-to-event and longitudinal data

Comparison of joint models for competing risks and longitudinal data

Supplementary material for the paper: A review on competing risks methods for survival analysis

Code and results of Section 4 of the paper "Fine-Gray subdistribution hazard models to simultaneously estimate the absolute risk of different event types: cumulative total failure probability may exceed 1", by Peter Austin, Ewout Steyerberg & Hein Putter

Code and supplementary materials for the manuscript "Multiple imputation for cause-specific Cox models: assessing methods for estimation and prediction" (2022, Statistical Methods in Medical Research)

Code accompanying the manuscript "Why you should avoid using multiple Fine–Gray models: insights from (attempts at) simulating proportional subdistribution hazards data" (2024, JRSS-A)

Code and supplementary materials for the manuscript "Joint models quantify associations between T-cell kinetics and allo-immunological events after allogeneic stem cell transplantation and subsequent donor lymphocyte infusion" (2023, Frontiers in Immunology)

MENSA: A Multi-Event Network for Survival Analysis under Informative Censoring (2024)

Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models in Stata

A Time-Dependent Structural Model Between Latent Classes and Competing Risks Outcomes

Code repository for the manuscript 'Multiple imputation of missing covariates when using the Fine–Gray model' (under review)

This repository includes the R code and data used in the analysis for the main manuscript of the paper. The cleaned data file consists of the data for only the 104 incident infections used. The ped.RDS file is an R data file for the piece-wise exponential data formulation of the survival data for the competing risks analysis. The descriptives fi…