Contributed Papers

Latest Topics in Causal Inference and Unmeasured Confounding

Mon, Aug 4, 10:30 AM - 12:20 PM Room CC-209C Music City Center

Lu LiChair

Biometrics Section

About this session

In this session, presenters will demonstrate latest advancements in modeling in causal inference as well as handling unmeasured confounding.

7 Presentations

Adaptive PoC and JS Test: An Adaptive Method for Power Enhancement in Causal Mediation Analysis

10:35 AM - 10:50 AM

Co-authors: ZITIAN ZHOU, Anxu Wang (Washington University in St. Louis), ZITIAN ZHOU, Sung Nok CHIU (Hong Kong Baptist University), Tiejun Tong (Hong Kong Baptist University), Nan Lin (Washington University in St. Louis)

Causal inference Mediation analysis Sobel test Adaptive test

Causal inference for observational studies with clustered survival outcomes subject to right-censoring

10:50 AM - 11:05 AM

Co-authors: Priyonto Saha, Priyonto Saha, Kuan Liu (University of Toronto)

Biostatistics Causal Inference Survival Analysis Longitudinal/Correlated Data Random Effects and Mixed Models Electronic Health Records

Properties of a Sensitivity Analysis for Causal Mediation and Path Analysis

11:05 AM - 11:20 AM

Co-authors: Jeffrey Albert (Case Western Reserve University), Jeffrey Albert (Case Western Reserve University), Carly Rose (Case Western Reserve University), Fang Wang (Case Western Reserve University), Yifei Xu (Case Western Reserve University), Ming Wang (Case Western Reserve University), Jang Ik Cho (Meta Platforms Inc., Reality Lab Health Technology)

causal inference generalized linear models path-specific effects sequential ignorability

Proximal Causal Inference for Contemporaneous Treatment Effect Estimation in Time Series Data

11:20 AM - 11:35 AM

Co-authors: Fanyu Cui (Columbia University), Charlotte Fowler, Fanyu Cui (Columbia University), Linda Valeri (Columbia University)

unmeasured confounding proximal causal inference time-series mhealth

Robust Bayesian Learning for Individualized Treatment Rules under Unmeasured Confounding

11:35 AM - 11:50 AM

Co-authors: Wei Jin (Johns Hopkins University), Wei Jin (Johns Hopkins University), Yang Ni (Texas A&M University), Yanxun Xu (Johns Hopkins University)

Causal identification Conservative policy optimization Individualized treatment rules Precision medicine Unmeasured confounding

Sensitivity analysis for unmeasured confounding with high-dimensional outcomes via outcome reduction

11:50 AM - 12:05 PM

Co-authors: Kwangmoon Park (University of Pennsylvania), Kwangmoon Park (University of Pennsylvania), Hyunseung Kang (University of Wisconsin-Madison), Kirk Hogan (University of Wisconsin-Madison), Reid Alisch (University of Wisconsin-Madison), Sunduz Keles (University of Wisconsin-Madison)

Sensitivity analysis Unmeasured confounding Dimension reduction epigenomics DNA methylation Alzheimer's disease

Simultaneous Estimation of Multiple Treatment Effects from Observational Studies

12:05 PM - 12:20 PM

Co-authors: XIAOCHUAN SHI, XIAOCHUAN SHI, Dehan Kong (University of Toronto), Linbo Wang (University of Toronto)

Causal inference Identification Sparsity assumption Unmeasured confounding.