40 citations · 129 across the 14 of their papers we have counts for
15 papers
Bayesian Variable Selection for High-Dimensional Predictors with Missing Psychometric Outcomes
Zongyue Teng, Shujie Ma, Timothy J. Hohman +2
High-dimensional, multimodal predictors and partially observed multivariate outcomes are common in psychometric research. However, existing regularization methods often do not acco…
Sensitivity Analysis for Causal Decomposition Analysis: Assessing Robustness Toward Omitted Variable Bias
Soojin Park, Suyeon Kang, Chioun Lee +1
A key objective of decomposition analysis is to identify a factor (the 'mediator') contributing to disparities in an outcome between social groups. In decomposition analysis, a sch…
Nearly Optimal Learning using Sparse Deep ReLU Networks in Regularized Empirical Risk Minimization with Lipschitz Loss
Ke Huang, Mingming Liu, Shujie Ma
We propose a sparse deep ReLU network (SDRN) estimator of the regression function obtained from regularized empirical risk minimization with a Lipschitz loss function. Our framewor…
A fusion learning method to subgroup analysis of Alzheimer's disease
Mingming Liu, Jing Yang, Yushi Liu +4
Uncovering the heterogeneity in the disease progression of Alzheimer's is a key factor to disease understanding and treatment development, so that interventions can be tailored to…
Causal Inference of General Treatment Effects using Neural Networks with A Diverging Number of Confounders
Xiaohong Chen, Ying Liu, Shujie Ma +1
Semiparametric efficient estimation of various multi-valued causal effects, including quantile treatment effects, is important in economic, biomedical, and other social sciences. U…
Detecting Latent Communities in Network Formation Models
Shujie Ma, Liangjun Su, Yichong Zhang
This paper proposes a logistic undirected network formation model which allows for assortative matching on observed individual characteristics and the presence of edge-wise fixed e…