News & Events
RCMAR Workshop: March 20, 2026
The Texas RCMAR Analysis Core and UTMB’s Department of Biostatistics and Data Science will host a free virtual workshop on March 20, 2026, focused on “Handling Survey Weights and Missing Data in Applied Survey Research.” Led by experts Xiaoying Yu, PhD, Jeong Hoon Jang, PhD, and Moumita Chakraborty, PhD, the event will guide participants through key methods for analyzing complex survey data.
This workshop provides a practical introduction to handling survey weights and missing data in applied survey analysis. Topics include complex sampling designs, appropriate use of weights, modern imputation techniques, approaches to non‑random missingness, and Bayesian methods for missing data. Nationally representative datasets such as NHANES and HRS will be used for demonstration. Participants will gain conceptual understanding and practical skills to strengthen their survey‑based research.
Date: March 20, 2026
Time: 10:00 AM — 3:00 PM CDT
Location: Teams
Sponsor: Texas Resource Center on Minority Aging Research (RCMAR) Analysis Core
Host: UTMB Department of Biostatistics and Data Science
Cost: FREE!
Workshop Schedule
Session 1: Introduction to Survey Data Analysis (10:00 — 11:00 AM CDT)
Instructor: Xiaoying Yu, PhD, Associate Professor
- Overview of complex survey designs (strata, clusters, weights)
- How to use sampling weights
- Common pitfalls in analyzing survey data
Session 2: Imputation for Missing Data (11:00 AM — 12:00 PM CDT)
Instructor: Jeong Hoon Jang, PhD, Assistant Professor
- Types of missing data (MCAR, MAR, MNAR)
- Single imputation (regression imputation, hot-deck imputation)
- Introduction to multiple imputation and key steps in practice
Lunch break: 12:00 — 1:00 PM CDT
Session 3: Handling Missing Not at Random (MNAR) (1:00 — 2:00 PM CDT)
Instructor: Jeong Hoon Jang, PhD, Assistant Professor
- Why MNAR is challenging in practice
- Sensitivity analysis for missing data assumptions
- Conceptual approaches to MNAR modeling (selection model, pattern-mixture model)
Session 4: Bayesian Methods in Missing Data Analysis (2:00 - 3:00 PM CDT)
Instructor: Moumita Chakraborty, PhD, Assistant Professor
- Bayesian framework with hierarchical modeling of missing data and model parameters
- Iterative methods for Bayesian multiple imputation and inference using the EM algorithm and Gibbs sampling
- Strategies for handling MNAR in the Bayesian framework
- Sensitivity analysis with respect to (1) prior distribution (2) missing data assumptions
Contact Us
Sealy Center on Aging (SCOA)
301 University Blvd.
Galveston, TX 77555-0177
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Phone: (409) 747-0008
Email: aging.research@utmb.edu