TY - JOUR
T1 - An introduction to joint models-applications in nephrology
AU - Chesnaye, Nicholas C.
AU - Tripepi, Giovanni
AU - Dekker, Friedo W.
AU - Zoccali, Carmine
AU - Zwinderman, Aeilko H.
AU - Jager, Kitty J.
PY - 2020/4
Y1 - 2020/4
N2 - 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.
AB - 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.
UR - https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85084429515&origin=inward
U2 - https://doi.org/10.1093/ckj/sfaa024
DO - https://doi.org/10.1093/ckj/sfaa024
M3 - Review article
C2 - 32296517
SN - 2048-8505
VL - 13
SP - 143
EP - 149
JO - Clinical Kidney Journal
JF - Clinical Kidney Journal
IS - 2
ER -