4 papers
A Bayesian machine learning approach to direct and spillover effects in cluster-randomized trials with noncompliance
Saurabh Bhandari, Fan Li, Michael J. Daniels
We develop a Bayesian machine learning approach for estimating direct and spillover effects in cluster-randomized trials with treatment noncompliance. To flexibly model outcomes an…
Causal mediation analysis for zero-inflated longitudinal data in the presence of treatment non-compliance and multiple mediators
Saurabh Bhandari, Wreetabrata Kar, Michael J. Daniels +1
Understanding whether a digital marketing campaign is effective is central to designing effective customer engagement strategies. We analyze a large-scale, longitudinal promotional…
Integrating tumor burden with survival outcome for treatment effect evaluation in oncology trials
Saurabh Bhandari, Michael J. Daniels, Chenguang Wang
In early-phase cancer clinical trials, the limited availability of data presents significant challenges in developing a framework to efficiently quantify treatment effectiveness. T…
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…