activity
20162020
most citedBayesian additive regression trees and the General BART model

115 citations · 132 across the 4 of their papers we have counts for

collaborators

5 papers

stat.AP2020★ 1 cited

Estimating the impact of treatment compliance over time on smoking cessation using data from ecological momentary assessments (EMA)

Yaoyuan Vincent Tan, Donna Coffman, Megan Piper +1

The Wisconsin Smoker's Health Study (WSHS2) was a longitudinal trial conducted to compare the effectiveness of two commonly used smoking cessation treatments, varenicline and combi…

stat.AP2019★ 115 cited

Bayesian additive regression trees and the General BART model

Yaoyuan Vincent Tan, Jason Roy

Bayesian additive regression trees (BART) is a flexible prediction model/machine learning approach that has gained widespread popularity in recent years. As BART becomes more mains…

stat.AP2018★ 6 cited

Accounting for selection bias due to death in estimating the effect of wealth shock on cognition for the Health and Retirement Study

Yaoyuan Vincent Tan, Carol A. C. Flannagan, Lindsay R. Pool +1

The Health and Retirement Study is a longitudinal study of US adults enrolled at age 50 and older. We were interested in investigating the effect of a sudden large decline in wealt…

stat.AP2018★ 10 cited

"Robust-squared" Imputation Models Using BART

Yaoyuan V. Tan, Carol A. C. Flannagan, Michael R. Elliott

Examples of "doubly robust" estimator for missing data include augmented inverse probability weighting (AIPWT) models (Robins et al., 1994) and penalized splines of propensity pred…

stat.AP2016

Predicting human-driving behavior to help driverless vehicles drive: random intercept Bayesian Additive Regression Trees

Yaoyuan Vincent Tan, Carol A. C. Flannagan, Michael R. Elliott

The development of driverless vehicles has spurred the need to predict human driving behavior to facilitate interaction between driverless and human-driven vehicles. Predicting hum…