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GASP 2019 presentations

Government Advances in Statistical Programming conference

September 23, 2019

Session 1A: Using R to streamline analysis

Session 1B: Model selection/validation with statistical software

  • A glimpse into the “Electricity Initiative” at the U.S. Energy Information Administration, Greg Lawson (Energy Information Administration)
  • Tableau for Data Scientists, Joel Hutchison (Tableau)
  • Using Cross-Validation for Variable Selection in Generalized Linear Models with Complex Survey Data, Darryl Creel (RTI International)
  • Scalable Approximate Kernelized Logistic Regression in R with an Application to the Census of Agriculture, Jonathan Abernethy (USDA-NASS)

Session 2A: Python libraries for text analysis and to streamline production

  • Easy deep learning text classification with gobbli, Jason Nance (RTI International)
  • Using Natural Language Processing and Machine Learning to Process Open Text Field Comments in a Panel Study, Kristin Chen (Westat)
  • Using Active Learning Framework and Automated Machine Learning Algorithms to Code Open-ended Responses, Rosalynn Yang (Westat)

Session 2B: Using R and open source to automate for efficiency

  • R Data Packages of Multi-Reader Multi-Case Studies and Simulation Tools to Support the Development of Reader Performance Evaluation Methods, Si Wen (FDA)
  • Hierarchical models in the production of official statistics: a discussion of some practical aspects, Andreea Erciulescu (Westat)
  • Topic Modeling Consumer Complaints for Risk Analysis, Benjamin Bloom (Federal Reserve Board)
  • Beyond the Analysis: An Approach to Operationalizing Your Results using Open Source JavaScript Frameworks, Dylan Holt (Accenture Federal)

Session 2C: Lightning Round!

  • Complex Survey Variance Estimation and Design Effects in R using the Rstan and Survey packages, Matt Williams (NCSES/NSF)
  • Ensemble Models with Basketball, John Thomas (George Washington University)
  • Automating the Maintenance of Survey Frames, Elizabeth Willhide and Keith Finlay (Census Bureau)
  • Text Analysis of Death Certificate Records to Ascertain Drugs Involved in Deaths from the National Vital Statistics System, Merianne Spencer and Brigham Bastian (NCHS)

Session 3A: Data dashboards for quick monitoring and analysis

  • SMART: An Open Source Tool to Facilitate Auto-Coding, Caroline Kery (RTI International)
  • Power Up NASS Data Analytics with MS Power BI, Leanne Tang (USDA-NASS)
  • Think Outside of the Box(plot), Jerry Valerio (Tableau)
  • Modern Techniques for Exploring Text Data, Peter Baumgartner (RTI International)

Session 3B: Open source software for fast information

  • Faster Computation for Hierarchical Bayesian-Model Using Rcpp Packages, Lu Chen (USDA-NASS)
  • Asking Consumers about their Finances, Kimberly Kreiss and Mike Zabek (Federal Reserve Board)
  • Using Python, PostgreSQL and R to analyze NIBRS data from the Crime Data Explorer, Ian Thomas (RTI International)
  • Weight Calibration across Packages, Dr. Stanislav Kolenikov-(Abt Associates)

Session 3C: Lightning Round!

  • Create Interactive Motion Charts Using R Package GoogleVis, Bidong Liu (Data and Analytic Solutions, Inc.) and Zhengyi Fang (Social & Scientific Systems, Inc.)
  • Automating Occupational Profiles Using RMarkdown, McLeod Brown (BLS)
  • Using R to Automate the Development of Custom Reports in Word Format, Alexandra Gates and Mina Zheng (NORC at the University of Chicago)
  • Linking EEOC Case Investigation Records by Employer Name using Text Analytics, Ada Harris (U.S. Equal Employment Opportunity Commission)
  • Rapid Implementation of Test Design Using Python, David Oh (BLS)

Session 4A: Application of Python and other software for production

  • Analyze, visualize, and . . . itemize: Tax policy analysis with Tax-Cruncher, Peter Metz (American Enterprise Institute)
  • Synergy between remote sensing and machine learning for crop yield prediction, Luca Sartore (USDA-NASS)
  • Getting Started with Using Amazon Mechanical Turk to Label Data, Brandon Kopp (BLS)

Session 4B: Analysis using R-shiny and other open source software

  • Using R and Shiny Applications to Analyze and Visualize NAEP Assessment Data, Emmanuel Sikali, Michael Lee, Paul Bailey and Ting Zhang (American Institutes for Research and NCES)
  • A Tour of USDA NASS’s Decision Support System, Nathan Cruze (USDA-NASS)
  • Measuring the cost and impact of open source software as intangible capital, Gizem Korkmaz (University of Virginia)

Session 4C: Lightning Round!

  • Adaptivity of Media and Behavioral Modeling, Mitchell Shuey (Independent) 
  • What is the meaning of this? How natural language processing can analyze unstructured data, Kelsey Gray (Insight Policy Research)
  • Routine Automation and Replication of PowerPoint Presentations in Python, Elaine WilcoxCook (Insight Policy Research) 
  • An Exploratory Research on Optimization of CFS Sampling Design, Mehdi Hashemipour (BTS), with Julie Parker
  • Science of Visual Analysis – Beyond Statistics, Jerry Valerio (Tableau)