Tests for trends in vaccine efficacy by genetic distance
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Updated
Sep 28, 2017 - R
Tests for trends in vaccine efficacy by genetic distance
Comparison of joint models for competing risks and longitudinal data
Mixed proportional hazard competing risk model with the NPMLE
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/Data/Figure for "Facility profiling under competing risks using multivariate prognostic scores weighting"
A Time-Dependent Structural Model Between Latent Classes and Competing Risks Outcomes
Replication syntax for Öney Flores 2019
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)
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…
Simulating time-to-event data from parametric distributions, custom distributions, competing risk models and general multi-state models in Stata
R package for fitting joint models to time-to-event and longitudinal data
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)
Supplementary material for the paper: A review on competing risks methods for survival analysis
Targeted Learning for Survival Analysis
Code repository for the manuscript 'Validation of the performance of competing risks prediction models: a guide through modern methods' (published in BMJ)
Finite-Interval Forecasting Engine: Machine learning models for discrete-time survival analysis and multivariate time series forecasting
Resources for Survival Analysis
Code accompanying the manuscript "Why you should avoid using multiple Fine–Gray models: insights from (attempts at) simulating proportional subdistribution hazards data" (under review)
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