GPU accelerated estimation of a shared random effect joint model for dynamic prediction-Reference-Cited by-同舟云学术

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GPU accelerated estimation of a shared random effect joint model for dynamic prediction

Published:2022-10 Issue: Volume:174 Page:107528
ISSN:0167-9473
Container-title:Computational Statistics & Data Analysis
language:en
Short-container-title:Computational Statistics & Data Analysis

Author:

Wang Shikun^ORCID,Li Zhao,Lan Lan,Zhao Jieyi,Zheng W. Jim^ORCID,Li Liang^ORCID

Funder

National Institutes of Health

Cancer Prevention and Research Institute of Texas

Publisher

Elsevier BV

Subject

Applied Mathematics,Computational Theory and Mathematics,Computational Mathematics,Statistics and Probability

Reference45 articles.

1. Bayesian joint modelling of longitudinal and time to event data: a methodological review;Alsefri;BMC Med. Res. Methodol.,2020

2. Combined dynamic predictions using joint models of two longitudinal outcomes and competing risk data;Andrinopoulou;Stat. Methods Med. Res.,2015

3. Improved dynamic predictions from joint models of longitudinal and survival data with time-varying effects using p-splines;Andrinopoulou;Biometrics,2017

4. Joint modeling of longitudinal and survival data with missing and left-censored time-varying covariates;Chen;Stat. Med.,2014

5. Joint modeling of longitudinal and survival data;Crowther;Stata J.,2013

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