Developing clinical prediction models for nominal polytomous outcomes: a simulation study comparing available approaches

Alexander Pate; Richard D. Riley; Matthew Sperrin; Ben Van Calster; Jamie C. Sergeant; Niels Peek; Tjeerd van Staa; Mamas Mamas; Professor Gregory Lip; Martín O’Flaherty; Iain Buchan; Glen P. Martin

doi:10.21203/rs.3.rs-3121017/v1

Related publications

Preprint2023

Calibration plots for multistate risk predictions models: an overview and simulation comparing novel approaches

Alexander Pate, Matthew Sperrin, Richard D. Riley, Niels Peek, Tjeerd van Staa, Jamie C. Sergeant, Mamas A. Mamas, Professor Gregory Lip, Martín O ́Flaherty, Michael Barrowman, Iain Buchan, Glen P. Martin

Article2023

Developing prediction models to estimate the risk of two survival outcomes both occurring: A comparison of techniques

Alexander Pate, Matthew Sperrin, Richard D. Riley, Jamie C. Sergeant, Tjeerd van Staa, Niels Peek, Mamas A. Mamas, Professor Gregory Lip, Martín O’Flaherty, Iain Buchan, Glen P. Martin

Article2018

Hidden Markov Models Based Approaches to Long-Term Prediction for Granular Time Series

Hongyue Guo, Witold Pedrycz, Xiaodong Liu

Article2008

Longest Available Clinical Outcomes After Drug-Eluting Stent Implantation for Unprotected Left Main Coronary Artery Disease

Emanuele Meliga, Hector Manuel Garcia-Garcia, Marco Valgimigli, Alaide Chieffo, Giuseppe Biondi‐Zoccai, Andrew O. Maree, Stephen L. Cook, Lindsay Reardon, Claudio Moretti, Stefano De Servi, Igor F. Palacios, Stefan Windecker, Antonio Colombo, Ron van Domburg, Imad Sheiban, Patrick W. Serruys

Journal of the American College of Cardiology

Chapter in a book2011

Trigonometric Polynomial Higher Order Neural Network Group Models and Weighted Kernel Models for Financial Data Simulation and Prediction

Lei Zhang, Simeon Simoff, Jing Chun Zhang