5 citations · 14 across the 18 of their papers we have counts for
13 papers · 1 filter
Dirichlet process mixture models for the Analysis of Repeated Attempt Designs
Michael J. Daniels, Minji Lee, Wei Feng
In longitudinal studies, it is not uncommon to make multiple attempts to collect a measurement after baseline. Recording whether these attempts are successful provides useful infor…
A Bayesian Non-parametric Approach for Causal Mediation with a Post-treatment Confounder
Woojung Bae, Michael J. Daniels, Michael G. Perri
We propose a new Bayesian non-parametric (BNP) method for estimating the causal effects of mediation in the presence of a post-treatment confounder. We specify an enriched Dirichle…
A Bayesian nonparametric approach for causal inference with multiple mediators
Samrat Roy, Michael J. Daniels, Brendan J. Kelly +1
Mediation analysis with contemporaneously observed multiple mediators is an important area of causal inference. Recent approaches for multiple mediators are often based on parametr…
Flexible evaluation of surrogacy in Bayesian adaptive platform studies
Michael C Sachs, Erin E Gabriel, Alessio Crippa +1
Trial level surrogates are useful tools for improving the speed and cost effectiveness of trials, but surrogates that have not been properly evaluated can cause misleading results.…
Information Borrowing in Regression Models
Amy Zhang, Le Bao, Michael J. Daniels
Model development often takes data structure, subject matter considerations, model assumptions, and goodness of fit into consideration. To diagnose issues with any of these factors…
Variable Selection Using Bayesian Additive Regression Trees
Chuji Luo, Michael J. Daniels
Variable selection is an important statistical problem. This problem becomes more challenging when the candidate predictors are of mixed type (e.g. continuous and binary) and impac…
Inference for BART with Multinomial Outcomes
Yizhen Xu, Joseph W. Hogan, Michael J. Daniels +2
The multinomial probit Bayesian additive regression trees (MPBART) framework was proposed by Kindo et al. (KD), approximating the latent utilities in the multinomial probit (MNP) m…
A Bayesian semi-parametric approach for inference on the population partly conditional mean from longitudinal data with dropout
Maria Josefsson, Michael J. Daniels, Sara Pudas
Studies of memory trajectories using longitudinal data often result in highly non-representative samples due to selective study enrollment and attrition. An additional bias comes f…
Informed Pooled Testing with Quantitative Assays
Tao Liu, Joseph W Hogan, Wanning Su +3
Pooled testing is widely used for screening for viral or bacterial infections with low prevalence when individual testing is not cost-efficient. Pooled testing with qualitative ass…
Bayesian Methods for Multiple Mediators: Relating Principal Stratification and Causal Mediation in the Analysis of Power Plant Emission Controls
Chanmin Kim, Michael Daniels, Joseph Hogan +2
Emission control technologies installed on power plants are a key feature of many air pollution regulations in the US. While such regulations are predicated on the presumed relatio…
Bayesian Longitudinal Causal Inference in the Analysis of the Public Health Impact of Pollutant Emissions
Chanmin Kim, Corwin M Zigler, Michael J Daniels +2
Pollutant emissions from coal-burning power plants have been deemed to adversely impact ambient air quality and public health conditions. Despite the noticeable reduction in emissi…
Bayesian nonparametric generative models for causal inference with missing at random covariates
Jason Roy, Kirsten J Lum, Michael J. Daniels +3
We propose a general Bayesian nonparametric (BNP) approach to causal inference in the point treatment setting. The joint distribution of the observed data (outcome, treatment, and…
Comparing Biomarkers as Trial Level General Surrogates
Erin E. Gabriel, Michael J. Daniels, M. Elizabeth Halloran
An intermediate response measure that accurately predicts efficacy in a new setting can reduce trial cost and time to product licensure. In this paper, we define a trial level gene…