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Westat expertise will be in the spotlight at the 2024 Federal Committee on Statistical Methodology (FCSM) Research and Policy Conference to be held October 22-24 in Hyattsville, Maryland. The theme is the Relevance, Timeliness, and Integrity of Federal Statistics.
On Tuesday, October 22, at 11 am, Jeri Mulrow, Westat Vice President and Sector Lead, Data Solutions, will give the keynote speech: Federal Statistics: Building on the Past, Looking to the Future.
Our researchers will be presenting on a variety of key topics over the course of the conference, including new insights on nonresponse bias, changes in refusal reasons over time, harnessing paradata with machine learning, salvaging data from an incomplete sample, and more. Westat is an organizational sponsor for the conference and is hosting the continental breakfast on Tuesday at 8 am.
See below for a list of our presentations (staff in bold) and the conference program (PDF) for times and locations at the event.
Tuesday, October 22
Lloyd Hicks, Amy Lin, Yiting Long, and Keith Rust. (Presentation). Maximizing Overlap of NAEP School Samples to Optimize Both Trend and Cross-Sectional Estimates.
Xiaoshu Zhu, Steph Battan-Wraith, Vanessa Olivo, and Kerry Grace Morrissey. (Presentation). Paradata Analysis of Participant Recruitment and Retention for COVID Household Transmission Study.
Elizabeth Petraglia. (Presentation). Identifying Underserved Areas Using Administrative Child Passenger Safety Data.
Sabrina Zhang and Tom Krenzke. (Presentation). New Insights on the Nonresponse Bias Analysis for the National Assessment of Educational Progress.
Benjamin Schneider, Tamara Nimkoff, Andy Cruse, and Anthony Fucci. (Presentation). Equipping State Agency Staff to Analyze Nonresponse Bias in Federal Survey Programs.
Steven Fink, Matt Jans, Jill Fleming, Denise Schaar, Andrew Caporaso, Jason Clark, George Dixon, Susan Genoversa, and Minsun Riddles. (Presentation). Changes in Refusal Reasons Over Time in the National Health and Nutrition Examination Survey (2017-2023).
James McCall, Kelsey Gray, Matthew Ring, Breanna Wakar, Richard Griffiths, Rahul Shrivastava, Yiting Long, Robin Ferg, and Karmen Perry. (Presentation). Exploring the Efficacy of Live Survey Methods at the National Science Foundation.
Jack Zhou, Gizem Korkmaz, Ting Yan, Jill Carle, Ryan Hubbard, Rick Dulaney, and Brad Edwards. (Presentation). Harnessing Paradata with Machine Learning to Inform Data Collection.
Jill Carle, Tammy Cook, Rick Dulaney, Brad Edwards, and Jeannine Barget. (Presentation). The Field Data Collector Labor Force: Lessons from the Pandemic.
Wednesday, October 23
Ting Yan, Gizem Korkmaz, and David Cantor. (Presentation). Who Are the Careless Web Respondents Identified by Machine Learning?
Organizer: John Deke; Chair: Scott Cody; Discussant: Thomas Wei. (Session). Evidence-Based Bayesian Methods for More Precise Estimates and Useful Inference.
Andreea Erciulescu, Jianzhu Li, Tom Krenzke, and Machell Town. (Presentation). Hierarchical Bayes Small Area Estimation for County-Level Health Prevalence to Having a Personal Doctor.
Robyn Ferg, Tom Krenzke, and Minsun Riddles. (Presentation). Assessing Utility of Synthetic Data: Applications to the Survey of Doctoral Recipients and Census Transportation Planning Projects.
Thursday, October 24
Wendy Van de Kerckhove, Tom Krenzke, and Benjamin Schneider. (Presentation). Salvaging Data from an Incomplete Sample Through Statistical Data Integration.