3 papers
stat.ME2026
Modeling Multivariate Missingness with Tree Graphs and Conjugate Odds
Daniel Suen, Yen-Chi Chen
In this paper, we analyze a specific class of missing not at random (MNAR) assumptions called tree graphs, extending upon the work of pattern graphs. We build off previous work by…
stat.ME2026
Modeling Missing at Random Neuropsychological Test Scores Using a Mixture of Binomial Product Experts
Daniel Suen, Yen-Chi Chen
Multivariate bounded discrete data arises in many fields. In the setting of dementia studies, such data is collected when individuals complete neuropsychological tests. We outline…
stat.ME2025
Masking criteria for selecting an imputation model
Yanjiao Yang, Daniel Suen, Yen-Chi Chen
The masking-one-out (MOO) procedure, masking an observed entry and comparing it versus its imputed values, is a very common procedure for comparing imputation models. We study the…