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stat.ME2024
Joint Models for Handling Non-Ignorable Missing Data using Bayesian Additive Regression Trees: Application to Leaf Photosynthetic Traits Data
Yong Chen Goh, Wuu Kuang Soh, Andrew C. Parnell +1
Dealing with missing data poses significant challenges in predictive analysis, often leading to biased conclusions when oversimplified assumptions about the missing data process ar…
stat.ME2024★ 1 cited
Seemingly unrelated Bayesian additive regression trees for cost-effectiveness analyses in healthcare
Jonas Esser, Mateus Maia, Andrew C. Parnell +4
In recent years, theoretical results and simulation evidence have shown Bayesian additive regression trees to be a highly-effective method for nonparametric regression. Motivated b…