5 papers · 1 filter
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…
A Bayesian Approach for Nonignorable Dropout in Bivariate Longitudinal Models
Andrea Gabrio, Michael J. Daniels, Gianluca Baio
Longitudinal data collected in clinical trials are almost always incomplete due to some of the participants dropping out from the study during the planned follow-up. A common strat…
A case study of causal mediation using Bayesian nonparametrics and semiparametric corrections
Yuhua Zhang, Michael J. Daniels
We propose a Bayesian nonparametric approach using a truncated Enriched Dirichlet Process mixture (EDPM) model to estimate natural direct (NDE) and indirect (NIE) effects in causal…
Variational Bayes and Truncation approximations for Enriched Dirichlet process mixtures
Somnath Bhadra, Michael J. Daniels
A common impediment in conducting inference for Bayesian nonparametric models is either the need for complex MCMC algorithms and/or computational run-time for large datasets. We pr…
Causal mediation analysis for longitudinal and survival data in continuous time using Bayesian non-parametric joint models
Saurabh Bhandari, Michael J. Daniels, Juned Siddique
Observational cohort data is an important source of information for understanding the causal effects of treatments on survival and the degree to which these effects are mediated th…