e-journal

Joint latent class models for longitudinal and time-to-event data: A review

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Most statistical developments in the joint modelling area have focused on the shared random-effect
models that include characteristics of the longitudinal marker as predictors in the model for the timeto-
event. A less well-known approach is the joint latent class model which consists in assuming that a
latent class structure entirely captures the correlation between the longitudinal marker trajectory and
the risk of the event. Owing to its flexibility in modelling the dependency between the longitudinal
marker and the event time, as well as its ability to include covariates, the joint latent class model may
be particularly suited for prediction problems. This article aims at giving an overview of joint latent
class modelling, especially in the prediction context. The authors introduce the model, discuss
estimation and goodness-of-fit, and compare it with the shared random-effect model. Then, dynamic
predictive tools derived from joint latent class models, as well as measures to evaluate their dynamic
predictive accuracy, are presented. A detailed illustration of the methods is given in the context of the
prediction of prostate cancer recurrence after radiation therapy based on repeated measures of
Prostate Specific Antigen.

Keywords
Brier score, joint model, longitudinal data, mixture model, predictive accuracy, prognosis, prostate cancer

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Informasi Detail

Judul Seri

Statistical Methods in Medical Research

No. Panggil

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Penerbit

London : SAGE., 2014

Deskripsi Fisik

Statistical Methods in Medical Research 2014, Vol. 23(1) 74–90

Bahasa

English

ISBN/ISSN

DOI: 10.1177/0962280

Klasifikasi

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Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

2014, Vol. 23(1)

Subjek

STATISTIK

Info Detail Spesifik

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Pernyataan Tanggungjawab

agus

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