3 papers
stat.ME2026
Combining longitudinal cohort studies to examine cardiovascular risk factor trajectories across the adult lifespan
Zeynab Aghabazaz, Michael J Daniels, Hongyan Ning +2
We introduce a statistical framework for combining data from multiple large longitudinal cardiovascular cohorts to enable the study of long-term cardiovascular health starting in e…
stat.ME2025
A Joint Model of Longitudinal CVD Risk Factors, Medication Use, and Time-to-Terminal Events
Zeynab Aghabazaz, Michael J Daniels, Donald M Lloyd-Jones +1
We introduce a novel Bayesian approach for jointly modeling longitudinal cardiovascular disease (CVD) risk factor trajectories, medication use, and time-to-events. Our methodology…
stat.ME2024
A Bayesian semi-parametric approach to causal mediation for longitudinal mediators and time-to-event outcomes with application to a cardiovascular disease cohort study
Saurabh Bhandari, Michael J. Daniels, Maria Josefsson +2
Causal mediation analysis of observational data is an important tool for investigating the potential causal effects of medications on disease-related risk factors, and on time-to-d…