An introduction to joint models—applications in nephrology-Reference-Cited by-同舟云学术

An introduction to joint models—applications in nephrology

Published:2020-04-01 Issue:2 Volume:13 Page:143-149
ISSN:2048-8505
Container-title:Clinical Kidney Journal
language:en
Short-container-title:

Author:

Chesnaye Nicholas C¹,Tripepi Giovanni²,Dekker Friedo W³,Zoccali Carmine⁴,Zwinderman Aeilko H⁵,Jager Kitty J¹

Affiliation:

1. Department of Medical Informatics, ERA-EDTA Registry, Amsterdam University Medical Center, University of Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, The Netherlands

2. Research Unit of Epidemiology and Physiopathology of Renal Diseases and Hypertension, CNR-IFC of Reggio Calabria, Reggio Calabria, Italy

3. Department of Clinical Epidemiology, Leiden University Medical Center, Leiden, The Netherlands

4. CNR-IFC, Clinical Epidemiology of Renal Diseases and Hypertension, Reggio Calabria, Italy

5. Department of Clinical Epidemiology, Biostatistics & Bioinformatics, Amsterdam UMC, University of Amsterdam, Amsterdam, The Netherlands

Abstract

Abstract In nephrology, a great deal of information is measured repeatedly in patients over time, often alongside data on events of clinical interest. In this introductory article we discuss how these two types of data can be simultaneously analysed using the joint model (JM) framework, illustrated by clinical examples from nephrology. As classical survival analysis and linear mixed models form the two main components of the JM framework, we will also briefly revisit these techniques.

Publisher

Oxford University Press (OUP)

Subject

Transplantation,Nephrology

Link

http://academic.oup.com/ckj/article-pdf/13/2/143/33028090/sfaa024.pdf

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