The 2017 Joint Statistical Meetings will take place July 29 - August 3, 2017 in Baltimore, MD. Researchers affiliated with NCRN nodes participate in the program, and this page lists a "virtual" program of sessions and activities with such participation. NCRN-affiliated researchers are bolded, speakers are in italics.
Sunday, July 30:
Session:
Statistical Methods for Heterogeneous and Massive Remote Sensing Data
NCRN Speakers:
- Inference for Errors-In-Variables Models in the Presence of Spatial and Temporal Dependence with an Application to a Carbon Dioxide Remote Sensing Campaign — Bohai Zhang, University of Wollongong ; Noel Cressie, University of Wollongong ; Debra Wunch, University of Toronto
Session:
Data Science with Semiparametric Bayes
NCRN Speakers:
- Bayesian Causal Forests — Richard Hahn, University of Chicago ; Jared S Murray, Carnegie Mellon University ; Carlos Carvalho, University of Texas at Austin
- Semiparametric Approaches to Bayesian Inference in Binary Instrumental Variable Models — Jared S Murray, Carnegie Mellon University
Session:
Data, Linked Data and Model-Based Analytics in Social Science
NCRN Speakers:
- An Active Learning Approach to Record Linkage — Kayla Frisoli, Carnegie Mellon University ; Sam Ventura, Carnegie Mellon University ; Jared S Murray, Carnegie Mellon University ; Stephen Fienberg, Carnegie Mellon University
Monday, July 31:
Session:
Synthetic Data Sets for Statistical Disclosure Limitation (ADDED FEE) — Professional Development Continuing Education Course
- Instructor(s): Jörg Drechsler, Institute for Employment Research, Jerry Reiter, Department of Statistical Science, Duke University
Session:
Bayesian Models for Gaussian and Point Processes
NCRN Speakers:
- Bayesian Modeling and Decision Theory for Non-Homogeneous Poisson Point Processes — Jiaxun Chen, University of Missouri-Columbia ; Athanasios Micheas, Univ of Missouri- Columbia ; Scott H. Holan, University of Missouri
Session:
Computationally Intensive Methods for Estimation and Inference
NCRN Speakers:
- Efficient Solution of Large Fixed Effects Problems with Clustered Standard Errors — Thomas Balmat, Duke University ; Jerry Reiter, Department of Statistical Science, Duke University
Session:
SPEED: Government Statistics, Health Policy, and Marketing
NCRN Speakers:
- Child Abuse on Trial: a Statistical Analysis of Shaken Baby Syndrome — Maria Cuellar, Carnegie Mellon University
Tuesday, August 1:
Session:
Section on Statistics in Imaging
NCRN Speakers:
- A Fully Automatic Method for Comparison of Cartridge Cases — Xiao Hui Tai, Department of Statistics, Carnegie Mellon University ; William F Eddy, Carnegie Mellon University, Department of Statistics
Session:
Climate Statistics: Studies on the Physics and Impacts of Climate Change Using Data Science
NCRN Speakers:
- The Scale Enhanced Wild Bootstrap Method for Evaluating Climate Models Using Wavelets — Ansu Chatterjee, University of Minnesota ; Amy Braverman, Jet Propulsion Laboratory ; Megan Heyman, Rose-Hulman Institute of Technology ; Noel Cressie, University of Wollongong
Organizer(s): Christopher Wikle, University of Missouri
NCRN Speakers:
- Adaptive Ensemble Kalman Filters for Online Bayesian State and Parameter Estimation — Jonathan Stroud, Georgetown University ; Matthias Katzfuss, Texas A&M University ; Christopher Wikle, University of Missouri
- Nonlinear Dynamical Spatio-Temporal Models and Their Efficient Estimation — Christopher Wikle, University of Missouri
Session:
ENVR Student Paper Award Winners
NCRN Speakers:
- Hierarchical Spatio-Temporal Analog Forecasting Model for Nonlinear Ecological Processes — Patrick McDermott, University of Missouri ; Christopher Wikle, University of Missouri ; Joshua Millspaugh, University of Montana
Session:
Novel Approaches to First Statistics / Data Science Course
NCRN Speakers:
- Lessons Learned in Transitioning from "Intro to Statistics" to "Reasoning with Data" — Rebecca Nugent, Carnegie Mellon Statistics
Session:
The New Multiple Data Sources Paradigm for Federal Statistics: Progress and Prospects
NCRN Speakers:
- The New Multiple Data Sources Paradigm for Federal Statistics: Progress and Prospects
Penelists: Robert Groves, Georgetown University
Amy O'Hara, Stanford University
Premkumar Natarajan, University of Southern California
Jerry Reiter, Department of Statistical Science, Duke University
Session:
Nonparametric Saturated Methods to Handle Nonignorable Missing Data
Organizer(s): Mauricio Sadinle, Duke University
Chair(s): Jerry Reiter, Department of Statistical Science, Duke University
NCRN Speakers:
- Combining Identifying Assumptions to Handle Nonignorable Missing Data — Mauricio Sadinle, Duke University ; Jerry Reiter, Department of Statistical Science, Duke University
Session:
Current Themes in Record Linkage Research
NCRN Speakers:
- File linking with faulty matching information — Nicole Dalzell, Wake Forest University ; Jerry Reiter, Department of Statistical Science, Duke University ; Gale Boyd, Duke University
Wednesday, August 2:
Session:
Zika Is Here, and We Need Statistics
NCRN Speakers:
- A Statistical Approach to the SIR Model — Andersen Chang, Carnegie Mellon University ; William F Eddy, Carnegie Mellon University, Department of Statistics
- Statistical and Computational Tools for Creating Synthetic Ecosystems — Lee Richardson, Carnegie Mellon University ; William F Eddy, Carnegie Mellon University, Department of Statistics ; Sam Ventura, Carnegie Mellon University ; Shannon Gallagher, Carnegie Mellon
- Calibration and Evaluation of Agent-Based Models for Disease Modeling — Shannon Gallagher, Carnegie Mellon ; Sam Ventura, Carnegie Mellon University ; William F Eddy, Carnegie Mellon University, Department of Statistics
- Discussant: William F Eddy, Carnegie Mellon University, Department of Statistics
Session:
Differential Privacy in Statistical Agencies: Present and Future
Organizer(s): Lars Vilhuber, Cornell University
NCRN Speakers:
Experiences with Differentially Private Geocoded Administrative Data — Jörg Drechsler, Institute for Employment Research; Jordi Soria-Comas, Universitat Rovira i Virgili
Differential Private Sign and Significance for Regression Coefficients — Andres Felipe Barrientos, Duke University ; Jerry Reiter, Department of Statistical Science, Duke University ; Ashwin Machanavajjhala, Duke University ; Yan Chen, Duke University
Formal Privacy Methods Come to the U.S. Census Bureau's Flagship Products — John M Abowd, U.S. Census Bureau
Session:
Advances in Spatial and Spatio-Temporal Methodology with Applications to Official Statistics
Organizer(s): Scott H. Holan, University of Missouri
NCRN Speakers:
- Multivariate Spatio-Temporal Survey Fusion with Application to the American Community Survey and Local Area Unemployment Statistics — Scott H. Holan, University of Missouri ; Jonathan R Bradley, Florida State University ; Christopher Wikle, University of Missouri
- Estimating Distributions for Populations Within Nested Geographies with Public-Use Data — Matthew Simpson, University of Missouri - Columbia ; Scott H. Holan, University of Missouri ; Christopher Wikle, University of Missouri ; Jonathan R Bradley, Florida State University
- Generating Partially Synthetic Geocoded Public-Use Data with Decreased Disclosure Risk Using Differential Smoothing — Harrison Quick, Drexel University ; Scott H. Holan, University of Missouri ; Christopher Wikle, University of Missouri
- An R Package for Spatio-Temporal Change of Support — Andrew Raim, U.S. Census Bureau ; Scott H. Holan, University of Missouri ; Jonathan R Bradley, Florida State University ; Christopher Wikle, University of Missouri
- Hierarchical Models for Spatial Data with Errors That Are Correlated with the Latent Process — Jonathan R Bradley, Florida State University ; Christopher Wikle, University of Missouri ; Scott H. Holan, University of Missouri
Session:
Memorial Session for Emanuel Parzen
Organizer(s): Scott H. Holan, University of Missouri
NCRN Speakers:
- Cepstral Models: An Overview of Recent Advances — Scott H. Holan, University of Missouri
Session:
Multiple Imputation for Measurement Errors and Other Structured Patterns of Missing Data
NCRN Speakers:
- Data Fusion for Correcting Measurement Errors — Maria DeYoreo ; Jerry Reiter, Department of Statistical Science, Duke University ; Tracy Schifeling, Duke
Thursday, August 3:
Session:
Recent Advances in High-Frequency and High-Dimensional Time Series
Organizer(s): Scott H. Holan, University of Missouri
NCRN Speakers:
- Dimension Reduction Approaches for Clustering Nonlinear/Nonstationary Time Series — Jane Harvill, Baylor University ; Scott H. Holan, University of Missouri ; Nalini Ravishanker, University of Connecticut
Session:
New Development for Causal Inference in Health Policy Statistics: a Bayesian Perspective
NCRN Speakers:
- Does Hospice Reduce End-Of-Life Medical Costs? Evidence from a Bayesian Analysis — Fan Li, Duke University ; Jerry Reiter, Department of Statistical Science, Duke University ; David Klemish, Duke University ; Don Taylor, Duke University
Session:
Environmental Epidemiology and Spatial Statistics
NCRN Speakers:
- Dynamic Spatial-Temporal Point Process Models via Conditioning — Athanasios Micheas, Univ of Missouri- Columbia ; Justin Okenye, University of Missouri ; Christopher Wikle, University of Missouri