Combined dynamic predictions using joint models of two longitudinal outcomes and competing risk data
Author:
Affiliation:
1. Department of Biostatistics, Erasmus MC, Rotterdam, The Netherlands
2. Department of Cardiothoracic Surgery, Erasmus MC, Rotterdam, The Netherlands
3. KU Leuven, L-Biostat, Leuven, Belgium
Abstract
Publisher
SAGE Publications
Subject
Health Information Management,Statistics and Probability,Epidemiology
Link
http://journals.sagepub.com/doi/pdf/10.1177/0962280215588340
Reference19 articles.
1. Individualized Predictions of Disease Progression Following Radiation Therapy for Prostate Cancer
2. Individual Prediction in Prostate Cancer Studies Using a Joint Longitudinal Survival–Cure Model
3. Development and validation of a dynamic prognostic tool for prostate cancer recurrence using repeated measures of posttreatment PSA: a joint modeling approach
4. Dynamic Predictions and Prospective Accuracy in Joint Models for Longitudinal and Time-to-Event Data
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