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stat.ME2026
Bayesian low-rank latent-cluster regression for mixed health outcomes
Hsin-Hsiung Huang, Suyeon Kang
High-dimensional health and surveillance studies often involve many collinear predictors, multiple correlated outcomes of different types, and latent heterogeneity across observati…
stat.ME2022
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…
stat.ME2021★ 1 cited
Choosing an Optimal Method for Causal Decomposition Analysis: A Better Practice for Identifying Contributing Factors to Health Disparities
Soojin Park, Suyeon Kang, Chioun Lee
Causal decomposition analysis provides a way to identify mediators that contribute to health disparities between marginalized and non-marginalized groups. In particular, the degree…