Mental Health Statistics Section Contributed Session 1

Tue, Aug 5, 2:00 PM - 3:50 PM Room CC-212 Music City Center

Wenzhu MowreyChair

Mental Health Statistics Section

About this session

Causal inference and machine learning in mental health

6 Presentations

A Calibrated Sensitivity Analysis for Weighted Causal Decompositions

2:05 PM - 2:20 PM

Co-authors: Andy Shen (UC Berkeley), Elina Visoki (Children's Hospital of Philadelphia), Andy Shen (UC Berkeley), Ran Barzilay (Children's Hospital of Philadelphia), Samuel Pimentel (University of California-Berkeley)

causal inference sensitivity analysis weighting health disparities observational studies causal decomposition analysis

A Machine Learning Framework Using Real-World Data to Unveil Heterogeneity in Schizophrenia Patients

2:20 PM - 2:35 PM

Co-authors: Handing Xie (Teva Pharmaceuticals), Olga Khanikova (Teva Pharmaceuticals), Handing Xie (Teva Pharmaceuticals), Sangtaeck Lim (Teva Pharmaceuticals), Weihsuan Lo-Ciganic (University of Pittsburg), Marc Tian

machine learning unsupervised clustering feature engineering real-world data schizophrenia personalized treatment

WITHDRAWN Durkheim's Social Integration Theory in Black Youth Suicide. A Machine Learning & Neighborhood Study

2:35 PM - 2:50 PM

Co-authors: Wenna Xi (Weill Cornell Medicine), Jialin Wu (Weill Cornell Medicine), Samprit Banerjee (Cornell University, Weill Medical College)

social integration Black youth suicide attempts electronic health records machine learning neighborhood effects

Identifiability and Inference for Generalized Latent Factor Models

2:50 PM - 3:05 PM

Co-authors: Chengyu Cui, Gongjun Xu (University of Michigan), Chengyu Cui

Maximum likelihood estimation Generalized factor model Limiting distributions

Individualized Treatment Effect on Factorized Multi-Domain Outcomes

3:05 PM - 3:20 PM

Co-authors: Wenbo Fei (Columbia University), Wenbo Fei (Columbia University), Molei Liu (Columbia University), Yuanjia Wang (Columbia University)

Adversarial learning Distributional robust Item response data Latent factor model Mental disorders Precision medicine

Using Structural Equation Modeling and Medicaid Data to Characterize the Hepatitis C Syndemic

3:20 PM - 3:35 PM

Co-authors: Angela Estadt (CDC), Angela Estadt (CDC), Michelle Van Handel (Office of the Director, National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention), Hasan Symum, William Thompson (Center for Disease Control & Prevention), Taiwo Abimbola (Office of the Director, National Center for HIV, Viral Hepatitis, STD, and Tuberculosis Prevention)

structural equation modeling factor model hepatitis C syndemic Medicaid