Sessions Were Renumbered as of May 19.
Legend:
CC-W = McCormick Place Convention Center, West Building,
CC-N = McCormick Place Convention Center, North Building
H = Hilton Chicago,
UC = Conference Chicago at University Center
* = applied session ! = JSM meeting theme
Activity Details
64 * !
Sun, 7/31/2016,
4:00 PM -
5:50 PM
CC-W184a
The World of Statistical Analysis Professionals — Topic Contributed Papers
Section for Statistical Programmers and Analysts , Section on Statistics in Marketing , Royal Statistical Society , International Chinese Statistical Association , Caucus for Women in Statistics
Organizer(s): Nancy C. Wang, Celerion
Chair(s): Nancy C. Wang, Celerion
4:05 PM
Personalized Marketing and the Role of the Statistician in Retail
—
Rebecca Schulthess, Eastbay/Footlocker.com
4:25 PM
When Analytics Meet Marketing: Statistics in Action with Marketing Data
—
Huimin Liu, Ocwen Financial
4:45 PM
Searching for Statistical Evidence of Better Health: Working as a Statistician on the Campus of a Major Academic Health Center
—
Harlan Sayles, University of Nebraska Medical Center
5:05 PM
What Can a Statistician Do at an Airline?
—
Aleksandra Stein
5:25 PM
Expanding the Use of Statistics at a Financial Institution
—
Kristin Carney, Cabela's
88
Sun, 7/31/2016,
6:00 PM -
8:00 PM
CC-Hall F1 West
The Extraordinary Power of Data — Invited Poster Presentations
Section on Statistical Learning and Data Science , Section on Statistical Graphics , Section on Statistics in Imaging , Business and Economic Statistics Section , Biometrics Section , ENAR , Section for Statistical Programmers and Analysts , Scientific and Public Affairs Advisory Committee , Section on Bayesian Statistical Science , Section on Statistics in Epidemiology , Section on Statistics in Marketing , Social Statistics Section , Statistics in Business Schools Interest Group
Chair(s): Tyler McCormick, University of Washington
1:
Communicate Better with R, R Markdown, and Shiny
—
Garrett Grolemund, RStudio
2:
Spectral Filtering for Spatial-Temporal Dynamics
—
Tian Zheng, Columbia University ; Lu Meng, Columbia University
3:
A Mixed-Effects Modeling Approach to Study the Impact of Pesticides on Farmworkers' Brain Networks Using RS-fMRI Data
—
Mohsen Bahrami, Virginia Tech ; Paul Laurienti, Wake Forest School of Medicine ; Thomas Arcury, Wake Forest School of Medicine ; Sean Simpson, Wake Forest School of Medicine
4:
Cascaded High-Dimensional Histograms: A Generative Approach to Density Estimation
—
Siong Thye Goh, MIT ; Cynthia Rudin, Duke University
5:
TV Advertising's Impact on Online Searches
—
Yonathan Schwarzkopf, Google ; Ying Liu, Google ; Makoto Uchida, Google ; Elissa Lee, Google ; Jim Koehler, Google
6:
Modeling Connectivity in High-Dimensional Time Series Data via Factor Analysis
—
Hernando Ombao, University of California at Irvine ; Yuxiao Wang, University of California at Irvine ; Chee-Ming Ting, Universiti Teknologi Malaysia
7:
Analysis of Longitudinal Multi-Sequence MRI in Multiple Sclerosis
—
Elizabeth M. Sweeney, Johns Hopkins Bloomberg School of Public Health ; Russell Shinohara, University of Pennsylvania ; John Muschelli, The Johns Hopkins University ; Daniel Reich , National Institute of Neurological Disorders and Stroke ; Ciprian Crainiceanu, The Johns Hopkins University ; Jonathan Gellar, Mathematica Policy Research ; Philip Reiss, New York University/University of Haifa ; Ani Eloyan, Brown University
8:
Law, Order, and Algorithms
—
Sharad Goel, Stanford University
9:
Defining and Estimating Reliability in Hierarchical Logistic Regression Models for Health Care Provider Profiling
—
Jessica Hwang, RAND Corporation ; John Adams, Kaiser Permanente ; Susan M. Paddock, RAND Corporation
10:
Probabilistic Cause-of-Death Assignment Using Verbal Autopsies
—
Tyler McCormick, University of Washington ; Sam Clark, University of Washington ; Zehang Li, University of Washington
11:
We Are What We Ask: Mapping the Ecosystem of Software Development Using Stack Overflow Data
—
David G. Robinson, Stack Overflow
12:
Data Science at Stitch Fix
—
Hilary Parker, Stitch Fix
13:
Text Mining on Domain Names
—
Kenneth E. Shirley, Amazon
14:
Fighting Fraud with Statistics!
—
Alyssa Frazee, Stripe
15:
Forecasting Seasonal Epidemics with Ensemble Methods and Collective Human Judgment
—
Logan Conrad Brooks, Carnegie Mellon University ; Sangwon Hyun, Carnegie Mellon University ; Ryan Tibshirani, Carnegie Mellon University
16:
Geometric Methods for Network Comparison and Multilevel Modeling
—
Anna Smith, The Ohio State University ; Catherine Calder, The Ohio State University
17:
Mixed-Effects Models for Resampled Network Statistics Improve Statistical Power to Find Differences in Functional Brain Connectivity
—
Manjari Narayan, Rice University ; Genevera Allen, Rice University
18:
Estimating the Causal Impact of Recommendation Systems from Observational Data
—
Amit Sharma, Microsoft Research ; Jake Hofman, Microsoft Research ; Duncan Watts, Microsoft Research
19:
The Future of the Journal Biostatistics
—
Dimitris Rizopoulos, Erasmus University Medical Center ; Jeffrey Leek, Johns Hopkins Bloomberg School of Public Health
20:
Sample Size Calculations for Micro-Randomized Trials in MHealth
—
Peng Liao, University of Michigan ; Ji Sun, University of Michigan ; Susan A. Murphy, University of Michigan
132
Mon, 8/1/2016,
8:30 AM -
10:20 AM
CC-W192a
Using Social Media, Text Mining, and Behavioral Data to Improve Marketing — Contributed Papers
Section on Statistics in Marketing
Chair(s): Qian Chen
8:35 AM
Social Signal Processing: Building Computational Models of Human Behavior in Digital Environments
—
William Rand, University of Maryland ; David Darmon, Uniformed Services University of the Health Sciences ; Michelle Girvan, University of Maryland
8:50 AM
An Online Prediction Framework of Influential Users During Urgent Events on Twitter
—
Hechao Sun
9:05 AM
Room for Improvement: Aspect-Specific Statistical Opinion-Mining of Online Hotel Reviews
—
Lynd Bacon, LBA/Northwestern University
9:35 AM
Competitive Intelligence: Text Mining Unstructured Data from the Internet of Things
—
James Wisnowski, Adsurgo LLC ; Andrew Karl, Adsurgo LLC
9:50 AM
Psychographic Market Segmentation with Very Large Number of Behavioral Factors
—
Atreyee Majumder, Michigan State University ; Tapabrata Maiti, Michigan State University
10:05 AM
Aggregate Propensity Matching in Market Research
—
Kurt Pflughoeft, MaritzCX ; Sharon Alberg, MaritzCX ; Kurt Salmela, MaritzCX ; Greg Blevins, MaritzCX
136
Mon, 8/1/2016,
8:30 AM -
10:20 AM
CC-W176b
Survey Modes, Including Web Surveys, Phone, and Multimode Surveys — Contributed Papers
Survey Research Methods Section , Section on Statistics in Marketing
Chair(s): Alfredo Navarro, Nielsen
8:35 AM
Estimated Prevalence and Characteristics of Web Users: National Health Interview Survey, 2014-2015
—
Meena Khare, CDC/NCHS
8:50 AM
Estimating Mail or Web Survey Eligibility for Undeliverable Addresses: A Latent Class Analysis Approach
—
Paul Biemer, RTI International ; Phil Kott, RTI International ; Joe Murphy, RTI International
9:05 AM
Evaluating the Effects of Adding Cell Phone Samples to the Traditional Landline Phone Samples on Prevalence Estimates from a Telephone Call-Back Survey
—
Xiaoting Qin, CDC ; Hatice S. Zahran, CDC ; Cathy M. Bailey, CDC
9:20 AM
Mail Versus Telephone Respondents in a Survey of Minority Populations
—
Youlian Liao, CDC
9:35 AM
What Paradata Can Tell Us About Online Data Reporting by Juvenile Residential Facilities
—
Suzanne Dorinski, U.S. Census Bureau
9:50 AM
Floor Discussion
155 !
Mon, 8/1/2016,
10:30 AM -
12:20 PM
CC-W196c
Causal Inference in a Networked World — Topic Contributed Papers
Section on Statistics in Marketing , IMS
Organizer(s): Edoardo M. Airoldi, Harvard
Chair(s): Daniel Sussman, Harvard
10:35 AM
Potential Outcome Regression with Interference
—
Joseph Rigdon, Stanford University ; Michael Hudgens, The University of North Carolina at Chapel Hill
10:55 AM
Peer Encouragement Designs in Causal Inference with Interference
—
Hyunseung Kang, Stanford University
11:15 AM
Model-Assisted Design of Experiments in the Presence of Network-Correlated Outcomes
—
Guillaume Basse, Harvard
11:35 AM
Matching Methods for Large Networks
—
Alexander Volfovsky, Harvard
11:55 AM
Inference in the Presence of Network Dependence Due to Contagion
—
Elizabeth Ogburn, The Johns Hopkins University
12:15 PM
Floor Discussion
186
Mon, 8/1/2016,
10:30 AM -
12:20 PM
CC-Hall F1 West
Topic-Contributed Poster Presentations: Government Statistics Section — Topic Contributed Poster Presentations
Government Statistics Section , Section on Statistics in Marketing
Chair(s): Nasrine Bendjilali, Rowan University
1:
Exploring the Gig Economy Using a Web-Based Survey: Measuring the Online 'and' Offline Side Work-for-Pay Activity+
—
Barbara J. Robles, Federal Reserve Board ; Marysol G. McGee, Federal Reserve Board
2:
Consumer Use of Mobile Financial Services: Results from the 2012--2015 Surveys and Reports
—
Alexandra Brown
3:
Survey of Household Economics and Decision Making (SHED): Statistical and Trend Analysis
—
Logan Thomas, Federal Reserve Board ; Anna Tranfaglia, Federal Reserve Board ; Jeff Larrimore, Federal Reserve Board ; Sam Dodini, Federal Reserve Board
4:
In the Shadow of the Great Recession: Experience and Perspectives of Young Workers
—
Barbara J. Robles, Federal Reserve Board ; Heidi Kaplan, Federal Reserve Board
233 *
Mon, 8/1/2016,
2:00 PM -
3:50 PM
CC-W184d
Statistics for Business Process Improvement — Topic Contributed Papers
Business and Economic Statistics Section , Section on Statistics in Marketing
Organizer(s): Beatriz E. Etchegaray Garcia, IBM Research
Chair(s): Beatriz E. Etchegaray Garcia, IBM Research
2:05 PM
Optimizing the Customer Experience Using Statistical Methods
—
Cheryl Flynn ; David Poole, AT&T Labs Research ; DeDe Paul, AT&T Labs Research
2:25 PM
Quantifying Tail Risk in Health Insurance Pools with Extreme Value Theory
—
Grant Weller, Savvysherpa
2:45 PM
Hierarchical Time Series Forecasting
—
Julie Novak, IBM ; Beatriz E. Etchegaray Garcia, IBM Research ; Yasuo Amemiya, IBM Research
3:05 PM
Floor Discussion
292 * !
Tue, 8/2/2016,
8:30 AM -
10:20 AM
CC-W183c
Online Experimentation: What Is It, Why Use It, and How to Do It Well? — Invited Papers
Section on Physical and Engineering Sciences , Section on Statistics in Marketing , Quality and Productivity Section
Organizer(s): Xinwei Deng, Virginia Tech
Chair(s): Xinwei Deng, Virginia Tech
8:35 AM
Multifactor Online Testing
—
David M. Steinberg, Tel Aviv University ; Tamar Haizler, Tel Aviv University
9:00 AM
Statistical Design for Online Experiments Across Desktops, Tablets, Smartphones (and Maybe Wearable Gadgets)
—
Peter Qian, University of Wisconsin - Madison ; Soheil Sadeghi, University of Wisconsin - Madison ; Neeraj Arora, University of Wisconsin - Madison
9:25 AM
How NOT to Do A/B Testing
—
David Charles Draper, University of California at Santa Cruz
9:50 AM
Discussant: David Woods, University of Southampton
10:10 AM
Floor Discussion
301 * !
Tue, 8/2/2016,
8:30 AM -
10:20 AM
CC-W184d
Statistical Challenges in Big Data, Finance, and Business Analytics — Topic Contributed Papers
Business and Economic Statistics Section , Section on Statistics in Marketing , Statistics in Business Schools Interest Group
Organizer(s): Kai-Sheng Song , University of North Texas
Chair(s): Ta-Hsin Li, IBM T. J. Watson Research Center
8:35 AM
Statistical Challenges in Big Data Analysis of the Hotel Industry
—
Kai-Sheng Song , University of North Texas
8:55 AM
Unsupervised Anomaly Detection in Time Series with Application in Electricity Demand Forecasting
—
Bei Chen, IBM Research ; Mathieu Sinn, IBM Research ; Ulrike Fischer , IBM Research
9:15 AM
Marketing Market Value at Risk
—
Zhengjun Zhang, University of Wisconsin - Madison ; Zhicheng Wang, Peking University ; Yu Chen, University of Science and Technology of China
9:35 AM
Least Tail-Trimmed Absolute Deviation Estimation for Autoregressions with Infinite/Finite Variance
—
Rongning Wu, Baruch College
9:55 AM
Floor Discussion
335 * !
Tue, 8/2/2016,
10:30 AM -
12:20 PM
CC-W190b
Statistics: The Secret Weapon of Web Giants — Invited Papers
Section on Statistics in Marketing
Organizer(s): Madeleine Cule, Google Life Sciences
Chair(s): Marianna Dizik, Google
10:35 AM
Creating Listener Segments at Pandora
—
Sam Lendle, Pandora
11:00 AM
Dealing with Credit Data: The Challenges and Statistical Solutions
—
Giulianna Perrotti dos Reis, Credit Sesame
11:25 AM
Friendship Paradoxes and the Quora Downvoting Paradox
—
Shankar Iyer, Quora ; Paula Griffin, Quora ; Olivia Angiuli, Quora
11:50 AM
Predictive Analytics in Internet Development
—
Alex Gilgur, Google/Alphabet ; Fred Xue, Google/Alphabet
12:15 PM
Floor Discussion
509 * !
Wed, 8/3/2016,
10:30 AM -
12:20 PM
CC-W195
Social Networks as the Unit of Observation — Invited Papers
Social Statistics Section , Section on Statistics in Marketing , Survey Research Methods Section
Organizer(s): Tracy Sweet, University of Maryland
Chair(s): Brian W. Junker, Carnegie Mellon University
10:35 AM
Using Feature Vectors to Cluster Social Networks
—
Tracy Sweet, University of Maryland ; David Sungjun Choi, Carnegie Mellon University ; Gabrielle Flynt, Bucknell University
11:00 AM
Modeling the Effects of Network Attributes on Subgroup Integration
—
Qiwen Zheng, University of Maryland
11:25 AM
Longitudinal Latent Space Network Model with VAR Evolution
—
Samrachana Adhikari, Carnegie Mellon University ; Brian W. Junker, Carnegie Mellon University
11:50 AM
Causal Mediation Analysis of Social Networks
—
Adam Chaim Sales, The University of Texas at Austin ; Tracy Sweet, University of Maryland ; Brian W. Junker, Carnegie Mellon University
12:15 PM
Floor Discussion
588 * !
Wed, 8/3/2016,
2:00 PM -
3:50 PM
CC-W183b
Estimation of Heterogeneous Treatment Effects — Invited Papers
Business and Economic Statistics Section , Section on Statistics in Marketing
Organizer(s): Craig A. Rolling, University of Oregon
Chair(s): Craig A. Rolling, University of Oregon
2:05 PM
Estimation and Inference of Treatment Effect Heterogeneity in Randomized Experiments
—
Max H. Farrell, The University of Chicago Booth School of Business
2:30 PM
Estimation and Inference of Heterogeneous Treatment Effects Using Random Forests
—
Susan Athey, Stanford University ; Stefan Wager, Stanford University
2:55 PM
Making Sense of Digital Experiments with Bayesian Nonparametrics
—
Matt Taddy, Chicago Booth
3:20 PM
Sufficient Dimension Reduction for Treatment Effect Estimation
—
Wenbo Wu, University of Oregon ; Craig A. Rolling, University of Oregon
3:45 PM
Floor Discussion
652
Thu, 8/4/2016,
8:30 AM -
10:20 AM
CC-W192b
Big Data and Data Science Education — Contributed Papers
Section on Statistical Education , Section on Statistics in Marketing , Statistics in Business Schools Interest Group
Chair(s): Gayla R. Olbricht, Missouri University of Science and Technology
8:35 AM
Teaching Students to Work with Big Data Through Visualizations
—
Shonda Kuiper, Grinnell College
8:50 AM
A Data Visualization Course for Undergraduate Data Science Students
—
Silas Bergen, Winona State University
9:05 AM
Intro Stats for Future Data Scientists
—
Brianna Heggeseth, Williams College ; Richard De Veaux, Williams College
9:20 AM
An Undergraduate Data Science Program
—
James Albert, Bowling Green State University ; Maria Rizzo, Bowling Green State University
9:35 AM
Modernizing an Undergraduate Multivariate Statistics Class
—
David Hitchcock, University of South Carolina ; Xiaoyan Lin, University of South Carolina ; Brian Habing, University of South Carolina
9:50 AM
Business Analytics and Implications for Applied Statistics Education
—
Samuel Woolford, Bentley University
10:05 AM
DataSurfing on the World Wide Web: Part 2
—
Robin Lock, St. Lawrence University
701
Thu, 8/4/2016,
10:30 AM -
12:20 PM
CC-W196a
Advanced Statistical Methods for Marketing — Contributed Papers
Section on Statistics in Marketing
Chair(s): William Rand, University of Maryland
10:35 AM
Using Random Forest to Create Adstock Predictors
—
Kathleen Bell, LB Personifi ; Scott Dachtyl, LB Personifi ; Rob Howie, Hallmark
10:50 AM
Weighted Dirichlet Process Mixture GARCH Model for Predicting Stock Price
—
Inyoung Kim, Virginia Tech ; Peng Sun, Virginia Tech
11:05 AM
Design and Analysis of Discrete Choice Experiments in the Presence of Profile Order Effects Within Choice Sets
—
Roselinde Kessels, University of Antwerp ; Robert Mee, University of Tennessee
11:20 AM
MaxDiff in Analytical Closed-Form Solution on Aggregate and Individual Levels
—
Stan Lipovetsky, GfK North America ; Michael W. Conklin, GfK North America
11:35 AM
Causal Models in Estimation of the Advertising
—
Igor Mandel, Telmar
11:50 AM
Does Improvement of Customer Satisfaction Always Create Shareholder Value? An Empirical Study of the American Customer Satisfaction Index
—
Qian Chen ; Duncan Fong, Penn State University ; Rui Wang, Peking University ; Zhe Chen, Google
12:05 PM
Scalable High-Performance Prediction with XGBoost
—
Ewa Nowakowska, GfK ; Joseph Retzer, ACT Market Research Solutions