Longitudinal data analysis encompasses a range of statistical methodologies that examine data collected over extended periods, enabling researchers to disentangle temporal effects and dynamic ...

Joint models are used in ageing studies to investigate the association between longitudinal markers and a time-to-event, and have been extended to multiple markers and/or competing risks. The ...

We propose Bayesian parametric and semiparametric partially linear regression methods to analyze the outcome-dependent follow-up data when the random time of a follow-up measurement of an individual ...

Joint models for longitudinal and survival data are particularly relevant to many cancer clinical trials and observational studies in which longitudinal biomarkers (eg, circulating tumor cells, immune ...

In a study published in the journal Nature Aging, researchers applied machine learning to analyze the health trajectories of healthy individuals over time and distinguish inherent aging factors from ...

The lectures on this page should be watched before the live sessions on Tuesday, June 14, 2022 (Wednesday, June 14 in some time zones). Total viewing time for this lecture series is 1 hour 40 minutes.