In longitudinal studies it is often of interest to investigate how a marker that is repeatedly
measured in time is associated with a time to an event of interest, eg, prostate cancer studies …

In longitudinal studies measurements are often collected on different types of outcomes for
each subject. These may include several longitudinally measured responses (such as blood …

A retrospective substudy of the nutritional prevention of cancer (NPC) trials investigated the
utility of longitudinally measured prostate-specific antigen (PSA) as a biomarker for …

Biological markers that are both sensitive and specific for tumour regrowth or metastasis are
increasingly becoming available and routinely monitored during the regular follow‐up of …

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 …

Patients treated for prostate cancer are monitored by periodically measuring prostate-
specific antigen (PSA) after treatment. Increases in PSA are suggestive of cancer recurrence …

Longitudinal studies often incur several problems that challenge standard statistical
methods for data analysis. These problems include non-ignorable missing data in …

Many scientific investigations generate both longitudinal data and survival data. Methods for
the combined analysis of both kinds of data have been developed in recent years, with the …

In this review, we present an overview of joint models for longitudinal and time-to-event data.
We introduce a generalized formulation for the joint model that incorporates multiple …

In biomedical and public health research, both repeated measures of biomarkers Y as well
as times T to key clinical events are often collected for a subject. The scientific question is …