4 papers
A Bayesian Nonparametric Approach for Semi-Competing Risks with Application to Cardiovascular Health
Karina Gelis-Cadena, Michael Daniels, Juned Siddique
We address causal estimation in semi-competing risks settings, where a non-terminal event may be precluded by one or more terminal events. We define a principal-stratification caus…
A Bayesian approach for unadjudicated events in cardiovascular disease cohort studies
Mirajul Islam, Michael J. Daniels, Donald Lloyd-Jones +1
An important issue in joint modelling for outcomes and longitudinal risk factors in cohort studies is to have an accurate assessment of events. Events determined based on ICD-9 cod…
Bayesian feature selection in joint models with application to a cardiovascular disease cohort study
Mirajul Islam, Michael J. Daniels, Zeynab Aghabazaz +1
Cardiovascular disease (CVD) cohorts collect data longitudinally to study the association between CVD risk factors and event times. An important area of scientific research is to b…
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…