4 papers
Emputation: Identification-Guided Neural Imputation Framework
Yanjiao Yang, Yikun Zhang, Xinwei Shen +1
We propose Emputation, a deep generative framework for learning imputation models. Emputation targets the extrapolation distribution of missing variables given observed variables,…
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…
Markov Missing Graph: A Graphical Approach for Missing Data Imputation
Yanjiao Yang, Yen-Chi Chen
We introduce the Markov missing graph (MMG), a novel framework that imputes missing data based on undirected graphs. MMG leverages conditional independence relationships to locally…
Imputation of Nonignorable Missing Data in Surveys Using Auxiliary Margins Via Hot Deck and Sequential Imputation
Yanjiao Yang, Jerome P. Reiter
Survey data collection often is plagued by unit and item nonresponse. To reduce reliance on strong assumptions about the missingness mechanisms, statisticians can use information a…