COVID-19 Impacts on the Post-Enumeration Survey
—
Shadie Khubba, U.S. Census Bureau; Elizabeth Marra, U.S. Census Bureau
Keywords: COVID-19; PES; census; measurement error
Nonresponse in the 2020 Post-Enumeration Survey (PES)
—
Shadie Khubba, U.S. Census Bureau; Mark Jost, US Census Bureau; Courtney Hill, U.S. Census Bureau
Keywords: nonresponse bias; unit nonresponse; 2020 Post-Enumeration Survey; Census Bureau
Analyzing the Imputations for Nonresponse in the 2020
Census Post-Enumeration Survey
—Michael Beaghen, U.S. Census Bureau;
Richard N. Turner, U.S. Census Bureau
Keywords: Census-coverage error, logistic regression
Bias in the Post-Enumeration Survey due to Duplicate
Misclassification (View Presentation)
—Scott Konicki, United States Census Bureau
Keywords: post-enumeration survey, coverage error, duplication
Research on Reducing Correlation Bias in Dual-System
Estimates
—Krista Heim, Decennial Statistical Studies Division;
Courtney Hill, Decennial Statistical Studies Division
Keywords: post-enumeration survey; dual system estimation; correlation bias; census; coverage; demographic analysis
Ahead of Its Time: Ken Brewer’s Influence on the Generalized Survey System at the Australian Bureau of Statistics
—Raymond Chambers, National Institute for Applied Statistics Research Australia
Keywords: Survey Sampling; Model-Based Inference; Generalized System; Model-Assisted Inference; Rotation Sampling; Heteroskedasticity
Developments in Sampling with Unequal Probabilities: Brewer's Contributions (View Presentation)
—J.N.K. Rao, Carleton University; David Haziza, University of Ottawa
Keywords: incluson probabilities; multistage sampling; primary sampling units
Ken Brewer’s Contributions to Survey Methodology
—Mike Hidiroglou, retired
Keywords: collocated sampling; permanent random number; systems
Ken Brewer and the Synthesis of Design and Model-Based Survey Sampling (View Presentation)
—Phillip S. Kott, RTI International
Keywords: collocated sampling; permanent random number; systems
Getting to Know Ken Brewer
—Timothy G Gregoire, Yale University
Keywords: Poisson sampling; forestry
Population Inference with Electronic Health Records (EHRs) Data: Addressing Selection and Representativeness Bias
—Yu B Chen, CDC
Sarah Conderino, NYU Grossman School of Medicine
Imaani Easthausen, Aetion
Emily Pfaff, University of North Carolina at Chapel Hill
Judy Zhong, New York University Grossman School of Medicine
Bo Cai, University of South Carolina, Arnold School of Public Health
Keywords: Electronic health records; public health surveillance; representativeness; misclassification; selection bias
Estimating SARS-CoV-2 Seroprevalence (View Presentation)
—Samuel P Rosin, University of North Carolina at Chapel Hill; Bonnie Shook-Sa, University of North Carolina - Chapel Hill; Stephen R Cole, UNC Chapel Hill; Michael Hudgens, University of North Carolina at Chapel Hill
Keywords: Covid-19; Diagnostic tests; Estimating equations; Seroepidemiologic studies; Standardization
Targeted Random Door-to-Door Sampling Design for COVID-19 Informed by Community Wastewater
—Katherine McLaughlin, Oregon State University
Keywords: design-based sampling; COVID-19; multistage sampling; probability sampling; prevalence estimation
Need Telephone Show Cards for Your In-Person Survey Due to a Pandemic-Induced Multimode Data Collection Shift? PATH Study Lessons Learned 2020 to Present…
—Victoria Castleman, Westat; Sarah Dipko, Westat
Keywords: COVID-19; Computer-Assisted Telephone Interviewing (CATI); Show cards; Instrument design; Multimode surveys
Testing a Probability-Based Online Panel Self-Administration of the Consumer Expenditure Diary Survey
—Nikki L. Graf, Bureau of Labor Statistics; Graham Jones, Bureau of Labor Statistics; Tucker Miller, Bureau of Labor Statistics; Wendy Carlton, Bureau of Labor Statistics; Ryan Tully, Ipsos
Keywords: online diaries; probability-based online panels; mode; data quality; expenditure diary
An Expanded Public Health Application of a Randomized Response Model Based on Applied Neuroscience
—Augustus Jayaraj, Cornell University; Sarjinder Singh, Texas A&M University-Kingsville; Oluseun Odumade, The Public Health Company
Keywords: Neuroscience; Randomized Response; Sensitive Data; Survey Sampling; Privacy Methods; Confidentiality Methods
Modeling State-Level Attitudinal Measures Related to
COVID-19 Vaccination of Children Using Survey Data
and Administrative Data
—N. Ganesh, NORC at the University of Chicago;
Shalima Zalsha, NORC at the University of Chicago;
Vicki Pineau, NORC at the University of Chicago;
Elizabeth Allen, NORC at the University of Chicago;
Zachary H. Seeskin, NORC at the University of Chicago;
Kirk M. Wolter1, NORC at the University of Chicago;
Tammy Santibanez, Centers for Disease Control and Prevention;
James A. Singleton, Centers for Disease Control and Prevention;
Michael Chen, Centers for Disease Control
and Prevention;
David Yankey, Centers for Disease Control
and Prevention;
Yi Mu, Centers for Disease Control
and Prevention;
Tianyi Zhou, Centers for Disease Control
and Prevention and Leidos Inc.;
Anurag Jain, Centers for Disease Control
and Prevention and Leidos Inc.
Keywords: COVID-19, composite estimation, National Immunization Survey, small
area estimation
Determination of Socio-Economic Effects of COVID-19 Pandemic in Turkey Using Logistic Regression
—Berna Yaz?c?, Eskisehir Technical University; Mustafa Çavu?, Eskisehir Technical University ; Emre Erdem, Eskisehir Technical University
Keywords: covid 19; Pandemic; Nominal Logistic Regression; Lockdown; Socio_Economic Effect
Deriving Measurements from Digital Trace Data: Opportunities and Challenges
—Ruben Bach, University of Mannheim; Christoph Kern, University of Mannheim
Keywords: Digital Trace Data; Combined Data; Survey Data; NLP
Measuring Facebook Use: The Accuracy of Self-Reported Data Versus Digital Trace Data
—Paulina Pankowska, Vrije Universiteit Amsterdam; Florian Keusch, University of Mannheim; Ruben Bach, University of Mannheim; Alexandru Cernat, University of Manchester
Keywords: Measurement error; Social media use; Digital trace data; Survey data; Data quality
Theorizing Personalization vs. Customization Effects in Digital Information Environments Using Survey and Behavioral Tracking Data
—Minh Hao Nguyen, University of Zurich
Keywords: digital trace data; survey; personalization; customization; online communication; mobile communication
Track Me, but Not Really: Tracking Undercoverage in Metered Data Collection
—Oriol J. Bosch, The London School of Economics and Political Science; Jouni Kuha, The London School of Economics and Political Science; Patrick Sturgis, The London School of Economics and Political Science
Keywords: Passive data; Data quality; Undercoverage; Measurement error; Digital trace data; Survey research
Online Decision-Making
—Gisoo Kim, UNIST
Keywords: bandit algorithms; machine learning; personalized interventions; statistical testing; actor-critic; robust tests
Building Innovative Ethical Health Care Systems via Sequential Approaches
—Jane Kim, Stanford University School of Medicine
Keywords: ethics; surveys; vignettes; sequential methods; artificial intelligence; health care
A Bayesian Decision-Theoretic Framework to Adaptively Estimate Minimum Effective Combinations of Sedentary Breaks to Reduce Cardiometabolic Risks: A Use Case of Adaptive Trial Design
—Ying Kuen Ken Cheung, Columbia University; Thevaa Chandereng, Columbia University; Keith M Diaz, Columbia University
Keywords: adaptive dose-finding; Bayesian decision-theory; glucose monitoring; posterior gain; sedentary breaks
Data Collection and Research Using the National Center for Health Statistics’ Research and Development Survey (RANDS)
—Paul Joseph Scanlon, National Center for Health Statistics
Keywords: commercial panels; web panels; official statistics; measurement error; data dissemination
New Measures for Assessing Non-Ignorable Selection Bias in Non-Probability Samples and Low Response Rate Probability Samples
—Brady Thomas West, Institute for Social Research, University of Michigan-Ann Arbor
Keywords: Selection Bias; Non-Ignorable Nonresponse; Non-Probability Sampling; Responsive Survey Design; Nonresponse Adjustment
Applying Calibration Weighting to Real-Time Surveys: Some Lessons Learned from the Research and Development Survey (RANDS)
—Yulei He, National Center for Health Statistics; Katherine Irimata, National Center for Health Statistics; Van Parsons, CDC; Bill Cai, CDC; Rebecca Hu, CDC; Rong Wei, CDC; Guangyu Zhang, CDC; Hee-Choon Shin, CDC
Keywords: Calibration; Raking; Propensity Score; Web Survey; Standardized Bias; Variable Selection
Producing Machine Learning Model-Based Health Estimates Using Web-Based Panel Data
—Katherine Irimata, National Center for Health Statistics; Ben Rogers, National Center for Health Statistics; Amy Cha, National Center for Health Statistics
Keywords: survey; weights; National Health Interview Survey; health
Rapid Surveys at the National Center for Health Statistics
—Jennifer Parker, National Center for Health Statistics; Stephen Blumberg, NCHS
Keywords: data integration; National Health Interview Survey; Research and Development Survey; web surveys
A Modern Infrastructure for the Future of Official Statistics: What Has Changed, and Where Are We Going?
—Anna Hui, Missouri Department of Labor and Industrial Relations;
Julia Lane, New York University;
Barry Johnson, Statistics of Income, IRS;
Nancy Potok, NAPx Consulting
Integrating Probability and Non-Probability Samples Through Machine Learning Based Methods
—Sixia Chen, University of Oklahoma Health Sciences Center; Chao Xu, University of Oklahoma Health Sciences Center; James Cutler, University of Oklahoma Health Sciences Center
Keywords: non-probability samples ; probability samples ; machine learning ; deep learning; generalized additive modeling
Functional Calibration Estimator for Non-Probability Sampling (View Presentation)
—Zhonglei Wang, Xiamen University; Jae-kwang Kim, Iowa State University; Xiaojun Mao, Shanghai Jiao Tong University
Keywords: Asymptotics; Missing at random; Nonparametric weighting; Reproducing kernel Hilbert space
Nationally Representative Absolute Risk Estimation Combining Individual Data from Epidemiologic Studies and Population-Based Surveys with Summary Statistics from Disease Registry
—Lingxiao Wang, National Cancer Institute, DCEG, Biostatistics Branch; Yan Li, University of Maryland, College Park; Barry Graubard , National Cancer Institute (NCI); Hormuzd Katki, National Cancer Institute
Keywords: risk prediction model; nonprobability cohort; finite population inference; propensity score weighting; Taylor series linearization variance
Embedded Multilevel Regression and Poststratification: Model-Based Inference with Incomplete Auxiliary Information
—Katherine Li, University of Michigan School of Public Health; Yajuan Si, University of Michigan
Keywords: incomplete poststratifiers; synthetic population; Bayesian bootstrap; sequential imputations
Analysis of Data Combined from Multiple Sources in the Presence of Linkage Error
—Martin Slawski, George Mason University; Brady Thomas West, Institute for Social Research, University of Michigan-Ann Arbor; Emanuel Ben-David, United States Census Bureau
Keywords: Record Linkage; Mismatch error; Pseudo-Likelihood ; Small Area Estimation
WITHDRAWN: Record Linkage: The Good, the Bad, and the Ugly
—Rebecca Steorts, Duke University
Keywords: record linkage; entity resolution; data integration; survey methodology ; privacy concerns; emerging issues
Surveys and Data Science: Oil and Water, or a Delicious Cocktail?
—Jean Opsomer, Westat
Statistical Data Integration Using Multilevel Models to Predict Employee Compensation (View Presentation)
—Andreea Luisa Erciulescu, Westat; Jean Opsomer, Westat; Benjamin Schneider, Westat
Keywords: granularity; hierarchical Bayes; multiple data sources; small area estimation; sparse survey data; data integration
Multiple Bias Calibration: A New Propensity Score Weighting Framework for Handling Selection Bias in Voluntary Samples
—Jae-kwang Kim, Iowa State University
Keywords: Empirical likelihood; Survey Sampling; Calibration
Incorporating Order Restrictions in Survey Domain Mean Estimation and Inference
—Mary C Meyer, Colorado State University; Xiyue Liao, California State University, Long Beach; Xiaoming Xu, Duke University; Jean Opsomer, Westat
Keywords: monotonicity; block monotonicity; covariance estimation
Inference in the Presence of Imputed Databased on Random Forests
—David Haziza, University of Ottawa; Mehdi Dagdoug, Université de Franche-Comté; Camelia Goga, Université de Franche Comté
Keywords: Nonparametric; High-dimensional; Variance estimation; Reverse approach ; Two-phase approach; Machine learning
Data Science Informed by Survey Science: Collecting More Accurate Labels
—Stephanie Eckman, RTI International; Jacob Beck, LMU; Frauke Kreuter, University of Maryland
Keywords: web survey; measurement error; data science; data labelling
Using Online Diary Paradata to Evaluate Diary Design and Usability
—Parvati Krishnamurty, Bureau of Labor Statistics; Brandon Kopp, Bureau of Labor Statistics; Graham Jones, Bureau of Labor Statistics
Keywords: paradata; online survey; online diary; mode
Can’t Go in Person? Consider Survey Reminder Mailings
—Chrystine Tadler, NORC at the University of Chicago; Melissa Heim-Viox, NORC at the University of Chicago
Keywords: Respondent Recruitment; Respondent Outreach; Telephone Intervieweing; Reminder Letter; Experiment
Reducing Response Bias in Reports of Trauma and
PTSD: An Application of the Nonverbal Response Card
in a Survey of Youth in Burkina Faso
—David P. Lindstrom, Brown University;
Guy Harling, University College London
Keywords: Trauma, PTSD, response mode, social desirability bias
Evaluating Methods to Adjust for Mode Effects in a Longitudinal Study
—Xiaoshu Zhu, Westat; Ting Yan, Westat
Keywords: Mode effects; Regression-based methods; Propensity score weighting; Multiple imputation; Longitudinal study
Improving Inferences Based on Survey Data Collected Using Mixed-Mode Designs
—Wenshan Yu, Michigan Program in Survey and Data Science, Institute for Social Research; Trivellore Eachambadi Raghunathan, University of Michigan; Michael Elliott, University of Michigan
Keywords: Mixed-mode inference; Model averaging; Bayesian; Testimator
WITHDRAWN: Disclosure Limitation for Surveys
—Rolando Andres Rodriguez, U.S. Census Bureau
Keywords: Disclosure limitation; Survey disclosure control; Census Bureau
Working with Stakeholders to Protect Data Confidentiality
—Aaron R. Williams, Urban Institute
Keywords: synthetic data; privacy; confidentiality; formal privacy
Expanding Data Access While Protecting Confidentiality
—Ellen Galantucci, Federal Maritime Commission
Keywords: confidentiality; data access; disclosure limitation
Survey of Economists’ Perspectives on Differentially Private Methods
—Joshua Snoke, RAND Corporation; Aaron R. Williams, Urban Institute; Claire McKay Bowen, Urban Institute; Andrés Barrientos
Keywords: Disclosure control; Differential Privacy; Survey data; Tax data; Validation server; Privacy
An Assessment of Privacy-Preserving Regression Analyses Within the Context of Validation Servers for Administrative Tax Data
—Andres F. Barrientos, Florida State University; Aaron R. Williams, Urban Institute; Joshua Snoke, RAND Corporation; Claire McKay Bowen, Urban Institute
Keywords: differential privacy; validation server; administrative data; regression
Spatial Kriging in the Presence of Informative Sampling Designs
—Erin Schliep, University of Missouri; Christopher K. Wikle, University of Missouri; Ranadeep Daw, University of Missouri
Keywords: preferential sampling; composite likelihood
An Empirical Evaluation of Alternative Approaches to Adjusting for Attrition When Analyzing Longitudinal Survey Data
—Yajuan Si, University of Michigan
Keywords: Longitudinal trajectory modeling; selection bias; attrition; weighting
A Comparison of Design-Based and Model-Based Approaches for Finite Population Spatial Data
—Michael Dumelle, United States Environmental Protection Agency (USEPA); Matt Higham, St. Lawrence University; Jay Ver Hoef, National Oceanic and Atmospheric Administration (NOAA); Anthony Olsen, United States Environmental Protection Agency (USEPA); Lisa Madsen, Oregon State University
Keywords: Finite Population Block Kriging (FPBK); Generalized Random Tessellation Stratified (GRTS) algorithm; Local neighborhood variance estimator; Restricted Maximum Likelihood Estimation (REML); Spatially balanced sampling; Spatial covariance
Preferential Sampling in Opportunistic Citizen Science Data
—Becky Tang, Duke University; Alan E. Gelfand, Duke University
Keywords: Geostatistical model; intensity function; log Gaussian Cox process; preferential sampling; nonhomogeneous Poisson process
Dynamic Models for Corporate Competitiveness of Global Health Care Industry with Mixed Effects
—Becky Tang, Duke University; Alan E. Gelfand, Duke University
Keywords: Dynamic models; Healthcare industry; Mixed effects; Online predictions; Corporate competitiveness; COVID-19 repercussions
A Mixed Model Approach for Dynamic Trade Networks
—Burcu Eke Rubini, University of New Hampshire; Loris Rubini, University of New Hampshire
Keywords: dynamic networks; international trade; relational data; network analysis
Using R Packages for Weekly Seasonal Adjustment
—Brian Carl Monsell, Bureau of Labor Statistics
Keywords: High-frequency time series; Signal extraction; Outlier identification
Privacy Secure Aggregation of the Individual Models into a Federated Model with Bayesian MCMC Bootstrapping
—Eugene Yankovsky, EY; Ana Yankovsky, Inuitive Surgical
Keywords: privacy protection; federated model; Bayesian MCMC; bootstrapping; Monte Carlo Markov Chain methods; Differential Privacy
The Inequality Process (IP) as Statistical Mechanics: How the IP’s Internal Model Enables Symmetries, Frame Independence, and the Search for the IP's Lagrangian Analogue
—John Angle, The Inequality Process Institute
Keywords: asymmetries; frame independence; Lagrangian; particle system; statistical mechanics; symmetries
Adapting COVID-19 Early Release Data to Determine Impact of Opioid Use in Hospital Emergency Departments
—Salah Shaikh, National Center for Health Statistics (NCHS) - CDC
Keywords: Hospital Data; Opioid; Administrative data; COVID-19
Comparing Methods for Weighting to Extend Inferences from a Collection of Trials
—Nicole Schnitzler, The Ohio State University; Eloise E Kaizar, The Ohio State University
Keywords: Causal Inference; Meta-analysis; Randomized Controlled Trials; Weighting; Transportability ; Generalizability
Examining the Effects of Contamination Due to School Mobility on Efficacy of Stepped Wedge Designs
—Meredith McCormack-Mager, The Ohio State University; Abigail Shoben, The Ohio State University
Keywords: stepped wedge; cluster randomized trials; trial design; education; randomized controlled trials; contamination
Results of a Push-to-Web Protocol in a Survey of Commercial Buildings
—Katie Lewis, Energy Information Administration; Sarah Grady, Energy Information Administration; Lawrence Chrishelle, Energy Information Administration
Keywords: push-to-web; multi-mode; paradata; web survey; CAPI survey
Using Effect Sizes to Quantify the Difference Between Survival Functions
—Huan Wang, Division of Biometrics IX, OB/OTS/CDER, FDA
Keywords: push-to-web; multi-mode; paradata; web survey; CAPI survey
Model-Robust Experimentation Strategy for Estimation of Expensive Black-Box Functions with Mixed Quantitative and Qualitative Factors
—Gautham Sunder, Carlson School of Management; Christopher Nachtsheim, Carlson School of Management
Keywords: Black-box Optimization; Model Robust Designs; Bayesian Optimization; Sequential Experiments; Goodness-of-fit test
A Statistical Model Predicting Final Yield During Data Collection
—Rui Jiao, WESTAT; Daniel Guzman, META; Sabrina Zhang, Westat; Andrea Piesse, WESTAT
Keywords: response propensity; interim cases; logistic regression ; classification tree; calibration
WITHDRAWN An Empirical Evaluation of Probabilistic File Linking Techniques
—Gauri Kamat, Brown University; Roee Gutman, Brown University
Keywords: file linking; analysis
Extending MRP to Incorporate Variables with Unknown Distributions
—Brittany Marie Alexander, Ipsos Public Affairs
Keywords: MRP; bayesian; multilevel regression; survey methodology
Predicting Call Sequence Length in the Telephone Mode Using Prediction Algorithms
—Xinyu Zhang, University of Michigan; James Wagner, University of Michigan
Keywords: Cost prediction; Responsive survey design; Machine learning
A Modified Proportional Allocation Sampling Method for the Study of Respirator Use and Practices in U.S. Private Industries
—Danny Friel, U.S. Bureau of Labor Statistics; Michelle Myers, U.S. Bureau of Labor Statistics; Dee Zamora, U.S. Bureau of Labor Statistics; Xingyou Zhang, U.S. Bureau of Labor Statistics; Katherine N. Yoon, National Institute for Occupational Safety and Health; Megan Casey, National Institute for Occupational Safety and Health; Emily J. Haas, National Institute for Occupational Safety and Health
Keywords: data linkage; oversampling; sample design; stratification; proportional allocation
Synthetic Data Generation for Complex Surveys
— Shirley Mathur, Duke University; Jerome P. Reiter, Duke University
Keywords: confidentiality; disclosure; multiple imputation
WITHDRAWN Demographic Edit and Imputation for Multilevel Data from the FBI’s National Incident Based Reporting System
—Philip Lee, RTI; Amang Sukasih, RTI; Dan Liao, RTI; Marcus Berzofsky, RTI International; Alexia Cooper, RTI
Keywords: Missing Data; Administrative Data; Crime Statistics; Hot Deck; Predictive Mean Matching
Evaluating the Use of Design Weights in Classification
Trees for Modeling Survey Nonresponse
—Tien-Huan Lin, Westat;
William Cecere, Westat;
Michael Jones, Westat;
Jennifer Kali1, Westat
Keywords: classification trees, nonresponse bias, response propensities, design weights, survey weights
Uncertainty Assessment of Finite-Population Medians Under Complex Sampling Designs
—Luca Sartore, National Institute of Statistical Sciences; Habtamu Benecha, USDA National Agricultural Statistics Service; Valbona Bejleri, USDA National Agricultural Statistics Service; Lu Chen, NISS/NASS, USDA
Keywords: Median estimator; Uncertainty; Complex sampling designs; Accuracy; Precision; Computational efficiency
Bias Interrupters Developed Estimators’ Network (BIDEN) with a Mixture of TRUMP Cuts and Jackknifing (View Presentation)
—Sarjinder Singh, Texas A&M University-Kingsville; Stephen A. Sedory, Texas A&M University-Kingsville
Keywords: Median estimator; Uncertainty; Complex sampling designs; Accuracy; Precision; Computational efficiency
Assessing Differences of Estimates Across Partial Overlapped Surveys Under Limited Design Information with Modified T-Tests
—Rong Wei, CDC; Van Parsons, CDC; Katherine Irimata, National Center for Health Statistics; Yulei He, National Center for Health Statistics
Keywords: Two sample test; Partial overlapped sample; Design-based; On-line survey; US population health
Overcoming the challenges of computing a single analysis weight when a state-level
component is incorporated into a traditional national-level study
Ruby E. Johnson,;
Peter H. Siegel,;
Kimberly Janda,;
Keywords: weighting; weight adjustments; poststratification; state-level data; NPSAS
Optimizing the Current Population Survey Composite Estimator(View Presentation)
—Justin McIllece, U.S. Bureau of Labor Statistics
Keywords: Current Population Survey; CPS; composite estimation; optimization; geometric series; variance estimation
Evaluating the First-Stage Sample Design for the 2020
Redesign of the Consumer Expenditures Surveys
—Stephen Ash, Bureau of Labor Statistics
Keywords: Two-stage sample design, variance estimation, balanced repeated replication variance estimator, collapsed-strata variance estimator
Comparing the 2019 American Housing Survey to Contemporary
Sources of Property Tax Records: Implications for Survey Efficiency
and Quality
—Ariel J. Binder, U.S. Census Bureau;
Emily Molfino, U.S. Department of Housing and Urban Development;
John Voorheis, U.S. Census Bureau;
Keywords: administrative records, third-party data, housing survey, item replacement and
supplementation, respondent burden
Understanding Self-Employment Income Data Quality in the American Community Survey
—John Voorheis, US Census Bureau
Keywords: Self Employment; Income; Administrative Records
Hierarchical Bayesian Model for County-Level Cash Rental Rates
—Lu Chen, National Institute of Statistical Sciences and USDA National Agricultural Statistics Service;
Balgobin Nandram, Worcester Polytechnic Institute and USDA National Agricultural Statistics Service
Keywords: Block Gibbs sampler, Grid method, Mixture model, Power prior, Outliers, Small area estimation, Survey
data
Bayesian Hierarchical Model for Combining Probability and Nonprobability Samples Under Unknown Overlaps
—Terrance D Savitsky, U.S. Bureau of Labor Statistics; Matthew R Williams, RTI International; Julie Gershunskaya, U.S. Bureau of Labor Statistics; Beresovsky Vladislav, NCHS
Keywords: Survey sampling; Inclusion probabilities; Bayesian hierarchical models; Nonrandom sample
Incorporating Administrative Data in Survey Weights for Federal Household Surveys
—Jonathan Eggleston, U.S. Census Bureau
Keywords: Weighting ; Administrative Data; Nonresponse
Borrowing Strength from Nearest Neighbors to Improve County-Level Estimates When Very Few or Zero Individuals Are Sampled
—Hui Xie, CDC; Deborah B Rolka, CDC; Yu B Chen, CDC
Keywords: Small area estimates (SAE); county-level; No sampled or too small sample size; machine learning
Using Geographically Weighted Regressions to Assess Variability in Small Area Model Parameters
—Jerry Joseph Maples, U.S. Census Bureau; Isaac Dompreh, U.S. Census Bureau
Keywords: Small Area ; Survey Data; Model Diagnostics
Mean Squared Error Estimation for Non-Normal Small Area Models
—Kyle M Irimata, U.S. Census Bureau; Jerry J Maples, U.S. Census Bureau; Gauri Sankar Datta, U.S. Census Bureau/University of Georgia
Keywords: Fay-herriot; Small area estimation; Census; Mean Squared Error
Evaluating a Sample Design for Small Area Estimation and Adaptive Field Efforts(View Presentation)
—Wendy Van de Kerckhove, Westat; Tom Krenzke, Westat
Keywords: Ohlsson; Keyfitz; Overlap control
Optimization of a Joint Confidence Region for a Ranking
—Tommy Wright, U.S. Census Bureau
Keywords: Independence (Sidak) Correction; Ranking Uncertainty; Official Statistics
Embracing cross-loading to improve latent variable models fit: A comparison of exploratory and Bayesian structural equation modeling
—Kevin B. Gittner, Kennesaw State University - Kennesaw, GA; Niloofar Ramezani, George Mason University; Katherine B. Mobley, Kennesaw State University - Kennesaw, GA
Keywords: Bayesian structural equation modeling; Exploratory structural equation modeling; Latent variable analysis; Factor cross loading; Multi-group measurement models
Dynamic Models for Corporate Competitiveness of Global Health Care Industry with Mixed Effects
—Mingzhao Hu, University of California, Santa Barbara; Lingdi Zhao, Ocean University of China; Danlei Feng, Ocean University of China
Keywords: Dynamic models; Healthcare industry; Mixed effects; Online predictions; Corporate competitiveness; COVID-19 repercussions
A Mixed Model Approach for Dynamic Trade Networks
—Burcu Eke Rubini, University of New Hampshire; Loris Rubini, University of New Hampshire
Keywords: dynamic networks; international trade; relational data; network analysis
Using R Packages for Weekly Seasonal Adjustment
—Brian Carl Monsell, Bureau of Labor Statistics
Keywords: dynamic networks; international trade; relational data; network analysis
Privacy Secure Aggregation of the Individual Models into a Federated Model with Bayesian MCMC Bootstrapping
—Eugene Yankovsky, EY; Ana Yankovsky, Inuitive Surgical
Keywords: privacy protection; federated model; Bayesian MCMC; bootstrapping; Monte Carlo Markov Chain methods; Differential Privacy
The Inequality Process (IP) as Statistical Mechanics: How the IP’s Internal Model Enables Symmetries, Frame Independence, and the Search for the IP's Lagrangian Analogue
—John Angle, The Inequality Process Institute
Keywords: asymmetries; frame independence; Lagrangian; particle system; statistical mechanics; symmetries
Adapting COVID-19 Early Release Data to Determine Impact of Opioid Use in Hospital Emergency Departments
—Salah Shaikh, National Center for Health Statistics (NCHS) - CDC
Keywords: Hospital Data; Opioid; Administrative data; COVID-19
Comparing Methods for Weighting to Extend Inferences from a Collection of Trials
—Nicole Schnitzler, The Ohio State University; Eloise E Kaizar, The Ohio State University
Keywords: Causal Inference; Meta-analysis; Randomized Controlled Trials; Weighting; Transportability ; Generalizability
Examining the Effects of Contamination Due to School Mobility on Efficacy of Stepped Wedge Designs
—Meredith McCormack-Mager, The Ohio State University; Abigail Shoben, The Ohio State University
Keywords: stepped wedge; cluster randomized trials; trial design; education; randomized controlled trials; contamination
Results of a Push-to-Web Protocol in a Survey of Commercial Buildings
—Katie Lewis, Energy Information Administration; Sarah Grady, Energy Information Administration; Lawrence Chrishelle, Energy Information Administration
Keywords: push-to-web; multi-mode; paradata; web survey; CAPI survey
Using Effect Sizes to Quantify the Difference Between Survival Functions
—Huan Wang, Division of Biometrics IX, OB/OTS/CDER, FDA
Keywords: effect size; survival analysis; test statistic; Mann-Whitney parameter
Model-Robust Experimentation Strategy for Estimation of Expensive Black-Box Functions with Mixed Quantitative and Qualitative Factors
—Gautham Sunder, Carlson School of Management; Christopher Nachtsheim, Carlson School of Management
Keywords: Black-box Optimization; Model Robust Designs; Bayesian Optimization; Sequential Experiments; Goodness-of-fit test
Specifying Prior Distributions in Reliability Applications —Colin Lewis-Beck, Eli Lilly; William Meeker, Iowa State; Qinglong Tian, University of Wisconsin ; Jarad Niemi, Iowa State
A Statistical Model Predicting Final Yield During Data Collection
—Rui Jiao, WESTAT; Daniel Guzman, META; Sabrina Zhang, Westat; Andrea Piesse, WESTAT
Keywords: response propensity; interim cases; logistic regression ; classification tree; calibration
WITHDRAWN An Empirical Evaluation of Probabilistic File Linking Techniques
—Gauri Kamat, Brown University; Roee Gutman, Brown University
Keywords: file linking; analysis
Extending MRP to Incorporate Variables with Unknown Distributions
—Brittany Marie Alexander, Ipsos Public Affairs
Keywords: MRP; bayesian; multilevel regression; survey methodology
Predicting Call Sequence Length in the Telephone Mode Using Prediction Algorithms
—Xinyu Zhang, University of Michigan; James Wagner, University of Michigan
Keywords: Cost prediction; Responsive survey design; Machine learning
A Modified Proportional Allocation Sampling Method for the Study of Respirator Use and Practices in U.S. Private Industries
—Danny Friel, U.S. Bureau of Labor Statistics; Michelle Myers, U.S. Bureau of Labor Statistics; Dee Zamora, U.S. Bureau of Labor Statistics; Xingyou Zhang, U.S. Bureau of Labor Statistics; Katherine N. Yoon, National Institute for Occupational Safety and Health; Megan Casey, National Institute for Occupational Safety and Health; Emily J. Haas, National Institute for Occupational Safety and Health
Keywords: data linkage; oversampling; sample design; stratification; proportional allocation
Synthetic Data Generation for Complex Surveys
—Shirley Mathur, Duke University; Jerome P. Reiter, Duke University
Keywords: confidentiality; disclosure; multiple imputation
WITHDRAWN Demographic Edit and Imputation for Multilevel Data from the FBI’s National Incident Based Reporting System
—Philip Lee, RTI; Amang Sukasih, RTI; Dan Liao, RTI; Marcus Berzofsky, RTI International; Alexia Cooper, RTI
Keywords: Missing Data; Administrative Data; Crime Statistics; Hot Deck; Predictive Mean Matching
Survey Research Methods Section P.M. Roundtable Discussion (Added Fee) — Roundtables PM Roundtable Discussion
—Carolina Franco, NORC at University of Chicago
Keywords: Bivariate; Small Area Estimation; Combining Surveys; Administrative Records; Borrowing Strength
A Review of Missing Data Approaches and Practices in Large Nationally Representative Survey Databases
—Parul Agarwal, Icahn School of Medicine at Mount Sinai
Keywords: missing data; survey data; data science; multiple imputation; large databases; research methods
Data-Driven Methods for Missing Data Imputation in Health Disparities Research
—Yuhao Zhang, George Washington University ; Yuxiao Huang , George Washington University ; Yan Ma, George Washington University
Keywords: missing data; machine learning ; class imbalance ; health disparities; data augmentation
Making Use of Summary Information from Large Databases Without Access to Their Individual Data
—Peisong Han, University of Michigan
Keywords: data integration; large databases; estimation efficiency; population heterogeneity; summary information
Are Deep Learning Models Superior for Missing Data Imputation in Large Surveys? Evidence from an Empirical Comparison
—OLANREWAJU MICHAEL AKANDE, Duke University; ZHENHUA WANG, University of Missouri; Jason Poulos, Harvard Medical School; Fan Li, Duke University
Keywords: data integration; large databases; estimation efficiency; population heterogeneity; summary information
Alternative Labor Market Surveys
—Bart Hobijn, Federal Reserve Bank of Chicago;
Chris Foote, Federal Reserve Bank of Boston;
Gizem Kosar, Federal Reserve Bank of New York
Keywords: Labor market statistics; survey methods
Record Linkage: Statistical Innovations to Advance Official Statistics
—Lisa B. Mirel, National Center for Health Statistics;
Jerome P. Reiter, Duke University;
Daniel Goroff, Alfred P. Sloan Foundation;
Aleksandra B. Slavkovic, Penn State University
Keywords: Official statistics; innovations; record linkage
A Consumption Measure for the U.S. Using Consumer Expenditure Data: Research and Development(View Presentation)
—Thesia I. Garner, Bureau of Labor Statistics
Keywords: consumption; Consumer Expenditures; flow of services
Measuring Energy Consumption in Commercial Buildings
—Tuncay Alparslan, U.S. Energy Information Administration
Keywords: Energy; Consumption; Commercial; Buildings
Rotating Panels for the Commercial Buildings Energy Consumption Survey: A Simulation Study
—Michael Joshua Winkler, U.S. Energy Information Administration; Janice Lent, U.S. Energy Information Administration; Caitlin Steiner, U.S. Energy Information Administration
Keywords: complex survey; energy consumption; simulation; rotating panel survey
Getting Time and Expenditure Together: Evaluating Imputation Methods for the Creation of Synthetic Data
—Fernando Rios-Avila, Levy Economics Institute; Thomas Masterson, Levy Economics Institute
Keywords: Time use; Expenditure; Imputation; Data Fusion
Getting Time and Expenditure Together: Evaluating Imputation Methods for the Creation of Synthetic Data
—Fernando Rios-Avila, Levy Economics Institute; Thomas Masterson, Levy Economics Institute
Keywords: Time use; Expenditure; Imputation; Data Fusion
Comparison of Poisson-Gamma and Laplace Mechanisms for Differential Privacy
—Harrison Quick, Drexel University
Keywords: Bayesian methods; Cancer mortality; Confidentiality; Disclosure risk; Spatial data
Computationally Efficient Bayesian Heteroskedastic Modeling for Small Area Estimation
—Paul A. Parker, University of California Santa Cruz; Scott H. Holan, University of Missouri/U.S. Census Bureau
Keywords: Gibbs Sampling; Mixed Models; Multivariate log-Gamma; Spatial; Volatility
Design Consistent Bayesian Tree Models
—Scott H. Holan, University of Missouri/U.S. Census Bureau; Diya Bhaduri, University of Missouri; Daniell Toth, U.S. Bureau of Labor Statistics
Keywords: Bayesian; Informative sampling; Survey methodology; Tree; Unit-level models
Hierarchical Bayesian Mixed Effect Models for Spatially Correlated Areal Multi-Distributional Survey Data When Covariates Are Measured with Error and Are Spatially Correlated
—Saikat Nandy, University of Missouri; Scott H. Holan, University of Missouri/U.S. Census Bureau; Jonathan R Bradley, Florida State University; Christopher K. Wikle, University of Missouri
Keywords: American Community Survey; Basis Function Expansion; Bayesian Hierarchical model; Generalized Transformation Model; Measurement error; Multi-distributional Response
Differentially Private Linear Regression with Linked Data via Gradient Descent
—Shurong Lin, Boston University; Eric Kolaczyk, Boston University
Keywords: differential privacy; record linkage; linear regression; gradient descent
Data Analysis After Record Linkage: Accounting for Mismatch Error via Mixture Models
—Zhenbang Wang, George Mason University; Guoqing Diao, George Washington University; Emanuel Ben-David, United States Census Bureau; Brady Thomas West, Institute for Social Research, University of Michigan-Ann Arbor; Martin Slawski, George Mason University
Keywords: record linkage; mixture models; pseudo-likelihood; EM algorithm
What Does This Mean for My Program?: Using Administrative Child Passenger Safety Data to Guide Policy (View Presentation)
—Elizabeth E Petraglia, Westat
Keywords: child passenger safety; administrative data; National Digital Car Seat Check Form; non-survey data
Automatic Imputation for an Area Survey(View Presentation)
—Tara Murphy, National Agricultural Statistics Service;
Arthur Rosales, National Agricultural Statistics Service;
Luca Sartore, National Agricultural Statistics Service and National Institute of Statistical Sciences;
Denise A. Abreu, National Agricultural Statistics Service
Keywords: nonresponse bias, unit nonresponse, 2020 Post-Enumeration Survey,
Census Bureau
Extending the Dual-system Estimation for the Census of Agriculture
—Habtamu Benecha, United States Department of Agriculture;
Luca Sartore, United States Department of Agriculture and National Institute of Statistical Sciences;
Grace Yoon, United States Department of Agriculture;
Bruce A. Craig, United States Department of Agriculture and Purdue University;
Denise A. Abreu, United States Department of Agriculture;
Linda J. Young, United States Department of Agriculture;
Keywords: Capture-recapture, Coverage, Non-response, Misclassification, List frame, Area
frame.
Application of Efficient Sampling with Prediction for Skewed Data
—James R. Knaub, Jr.
Keywords: Applications, Cost/Resources, Establishment surveys, Model-based approach, Official
Statistics, Prediction Approach, Quasi-cutoff sampling, Skewed data, Total survey error
An Algorithm for Small Area Estimation under Not Missing At
Random Non-response
—Michael Sverchkov, Bureau of Labor Statistics
Keywords: population distribution, respondents model, sample distribution
Modeling Changes in Physician Health After
Participation in the Leading Physician Well-Being
Certificate Program
—Elisabeth Callen, American Academy of Family Physicians;
Tarin Clay, American Academy of Family Physicians;
Heather Woods, American Academy of Family Physicians;
Margot Savoy, American Academy of Family Physicians;
Kat Istas, American Academy of Family Physicians;
Natabhona Mabachi, American Academy of Family Physicians
Keywords: Mixed Effect Regression, Physician Well-Being, Burnout, Quality
Improvement
Understanding the Role of Language and Culture in STEM Education
—Yanming Di, Oregon State University
Keywords: STEM; language; culture; survey; education
Divided We Poll, United We Pool: An Application of Multiple Imputation for Multiple Surveys
—Jui-Chung Allen Li, Quanthon Corporation; I-Ting Tsai, Quanthon Corporation; Fang-Yu Rona Hu, Quanthon Corporation
Keywords: survey nonresponse; multiple imputation; opinion poll; survey data quality; telephone survey; government statistics
Comparing Record Linkage Software: NorcLink Vs FastLink
—Jennifer Taub, NORC at the University of Chicago; Dean Resnick, NORC at the University of Chicago; Scott Campbell, NORC at the University of Chicago
Keywords: Record Linkage
Pretest Estimation in Combining Probability and Non-Probability Samples
—Chenyin Gao, North Carolina State University; Shu Yang, North Carolina State University
Keywords: Data integration; Dynamic borrowing; Non-regularity; Pretest estimator
Disclosure Limitation for Surveys
—John M Abowd, U.S. Census Bureau
Keywords: Disclosure limitation; Survey disclosure control; Census Bureau
Estimation Methods for Combining Probability and Nonprobability Samples
—Michael Yang, NORC at the University of Chicago
Keywords: nonprobability sample estimation
Revealed Preference Models for Separating Preferences and Availability Effects in Marriage Formation
—Mark Stephen Handcock, University of California - Los Angeles; Shuchi Goyal, University of California - Los Angeles; Michael S. Rendall, University of Maryland, College Park; Heide M. Jackson, University of Maryland, College Park
Keywords: Marriage model; Survey for Income and Program Participation; Two-sided logit; Two-sided matching; Social networks; relational data
Network Dependence Can Lead to Spurious Associations and Invalid Inference
—Youjin Lee, Brown University; Elizabeth Ogburn, Johns Hopkins University
Keywords: Autocorrelation; Social networks; Confounding; Replication; Statistical dependence
Measuring and Modeling Neighborhoods
—Cory McCartan, Harvard University; Kosuke Imai, Harvard University; Jacob Brown, Harvard University
Keywords: hierarchical model; Bayesian; residential segregation; surveys; measurement
Examining the Consumption of Extreme Content on Social and Mainstream Media
—Homa Hosseinmardi, University of Pennsylvania; David Rothschild, Microsoft Research
Keywords: News; Television; Online; Social Media; Radicalization; Polarization
Very Long-Term Global Population and Migration Projections for Assessing the Social Cost of Carbon
—Adrian E. Raftery, University of Washington
A-Optimal Split Questionnaire Designs for Multivariate Continuous Variables
—Dae-Gyu Jang, Iowa State University; Zhengyuan Zhu, Iowa State University; Cindy Yu, Iowa State University
Keywords: Survey Sampling; Survey Design; Probabilistic Design; Optimality Criterion
Sample Size Estimation in Respondent-Driven Sampling
—Yibo Wang, University of Michigan; Michael Elliott, University of Michigan; Sunghee Lee, University of Michigan, Institute for Social Research
Keywords: Respondent-Driven Sampling; sample size; recruitment success
Receiver Operating Characteristic Curve for Complex Survey Data
—Tamy Harumy Moraes Tsujimoto, University of North Carolina at Chapel Hill; Jianwen Cai, University of North Carolina at Chapel Hill
Keywords: Complex survey data; ROC curve; Horvitz-Thompson estimator; empirical processes
On the Reliability of Multiple Systems Estimation for the Quantification of Modern Slavery (View Presentation)
—Olivier Binette, Duke University; Rebecca Steorts, Duke University
Keywords: multiple systems estimation; capture-recapture; modern slavery
Smoothed Model-Assisted Small Area Estimation
—Peter A. Gao, University of Washington; Jon Wakefield, University of Washington
Keywords: small area estimation; survey statistics; spatial statistics; model-based geostatistics; demography; Bayesian statistics
Using Results from a Qualitative Study on Web Paradata to Create Quantitative Measures for Survey Design Improvement
—Renee Ellis, U.S. Census
Keywords: paradata; survey methods; machine learning; data science
Did We Make an Interviewer’s Job Easier? The Impact of the National Health Interview Survey Questionnaire Redesign on Interviewer Effects
—James M Dahlhamer, National Center for Health Statistics; Aaron Maitland, National Center for Health Statistics; Benjamin Zablotsky, National Center for Health Statistics; Antonia Warren, National Center for Health Statistics
Keywords: interviewer effects; questionnaire design; multilevel models
WITHDRAWN Impact of Low Quality Responses on Dimensionality of Scales
—Nivedita Bhaktha, GESIS; Clemens Lechner, GESIS
Keywords: Careless responses; Low quality responses; Simulation study; Inattentive responses; Random responses; Dimensionality
Survey Data Quality
—Ioannis Andreadis, Aristotle University of Thessaloniki; Andreas Andreadis, Aristotle University of Thessaloniki
Keywords: data quality; careless responses; data cleaning; web surveys; speeding
Propensity Models for Nonresponse Adjustments in Telephone Surveys
—Yangyang Deng, ICF Macro, Inc.; Ronaldo Iachan, ICF Macro, Inc; Randy ZuWallack, ICF Macro, Inc.; Adam Lee, ICF Macro, Inc.; Thomas Brassell, ICF Macro, Inc.
Keywords: Telephone Surveys; Non-response analysis; Multilevel Modeling; BRFSS; Weighting
Combining Probability and Nonprobability Samples by Using Latent Joint Multivariate Normal Model Mass Imputation
—Alexandra Milligan, University of Oklahoma Health Sciences Center; Sixia Chen, University of Oklahoma Health Sciences Center; Janis Campbell, University of Oklahoma Health Sciences Center
WITHDRAWN Imputation with Verifiable Identification Condition for Nonignorable Missing Data
—Kenji Beppu, Osaka University; Kosuke Morikawa, Osaka University; Jongho Im, Yonsei University
Keywords: Incomplete data; Not missing at random(NMAR); Identification; Multiple imputation; Fractional imputation
Use Machine Learning Approach to Assess Interviewer Performance
—Hanyu Sun, Westat; Ting Yan, Westat
Keywords: machine learning; interviewer performance; falsification
Evolving Official Estimates Using Data Science and Diverse Survey and Nonsurvey Data Sources
—Linda J Young, USDA National Agricultural Statistics Agency
Keywords: Sample survey; Data integration; Machine learning; Inference
Faster, Cheaper, Better: How the UK’s Office for National Statistics Is Using Data Science and Machine Learning to Strengthen Our Surveys
—Tom Smith, Office for National Statistics, UK; Arthur Turrell, Office for National Statistics, UK
Keywords: Data science; Surveys; Machine learning; Census; Covid
Surveys and Data Science at Statistics Canada
—Eric Rancourt, Statistics Canada
Keywords: Administrative Data; Big Data; Inference; Machine Learning; Non-Probabilistic
Oversampling of Minority Populations Through Dual-Frame Surveys
—Alexander Stubblefield, Michigan State University; Julie Stoner, University of Oklahoma Health Sciences Center; Sixia Chen, University of Oklahoma Health Sciences Center
Keywords: Oversampling; Minority; Stratification; Telephone Survey; Dual-Frame
Creating Multiple Synthetic Frames for Sample Design Research on the Business Enterprise Research and Development Survey
—Matthew R Williams, RTI International; Hang Kim, University of Cincinnati; Katherine J. Thompson, US Census Bureau; Stephen Kaputa, U.S. Census Bureau
Keywords: survey; synthetic data; mixture models; MCMC
Using Differentially Private Synthetic Data to Inform the Design Stage of a Sample Survey
—Marcel Neunhoeffer, Boston University; Katherine J. Thompson, US Census Bureau; Donald Mark Bauder, U.S. Census Bureau
Keywords: Synthetic Data; Informative Survey Design; Differential Privacy
Developing a Unified Sample Design for the Annual Integrated Economic Survey
—Katherine J. Thompson, US Census Bureau
Keywords: business survey; probability proportional to size; winsorization; power allocation
A Weighting Approach for Generalizing Big Data
—Michael Robbins, RAND Corporation
Keywords: Big Data; Twitter; Weighting; Political Sentiment; Probability Sample
Optimizing Data Collection Interventions to Balance Cost and Quality in a Sequential Multimode Survey
—Stephanie Coffey, US Census Bureau; Michael Elliott, University of Michigan
Keywords: adaptive design; responsive design; Bayesian methods; optimization; survey costs
Estimating the Size of Clustered Hidden Populations(View Presentation)
—Laura Jean Gamble, Westat; Katherine McLaughlin, Oregon State University
Keywords: Respondent-driven sampling; Successive sampling population size estimation; Hidden populations; Hard-to-reach populations; Network sampling
Comparison of Direct Estimation and Network Scale-Up Method for Prevalence Estimation of Child Trafficking in Sierra Leone
—Hui Yi, University of Georgia; Kyle Vincent, Independent Researcher and Consultant; David Okech, University of Georgia; Jody Clay-Warner, University of Georgia; Jiacheng Li, University of Georgia; Tenshi Kawashima, University of Georgia; Timothy Edgemon, Auburn University
Keywords: Child Labor; Child Trafficking; Direct Estimation; Household Survey; Network Scale-Up Method
Evaluating Substitution as a Strategy for Handling Drop Points in Self-Administered Address-Based Sampling Frame Surveys (View Presentation)
—Taylor H Lewis, RTI International; Joseph McMichael, RTI International; Charlotte Looby, RTI International
Keywords: Address-Based Sample; ABS; health survey; substitution
Using Simulation to Assess the Effect of Changes in Sample Size and the Number of Primary Sampling Units in a Health Survey
—Chris Moriarity, National Center for Health Statistics; Te-Ching Chen, National Center for Health Statistics
Keywords: sample survey
Forming Area Sampling Units with Geospatial Sorts, with Application to Counties and Census Blocks in PIAAC
—Benjamin Schneider, Westat; Tom Krenzke, Westat; Wendy Van de Kerckhove, Westat; Jennifer Kali, Westat; Ying Chen, Westat
Keywords: segments; clusters; in-person surveys; Travelling Salesman
Transitions from Telephone to Mixed Mode Surveys
—Kristen Olson, University of Nebraska At Lincoln
Keywords: Mixed mode surveys; Telephone Surveys; Web surveys; Mail surveys; Data Collection
Early Experiences When Transitioning from RDD to a Postal Mail Survey Using a Paper Questionnaire
—David Cantor, Westat
Keywords: Mode effects; Response rates
The Impact of an RDD to ABS/Mail Sample Design and Mode Change in the 2021 New York City Community Health Survey (CHS) (View Presentation)
—Michael Witt, Abt Associates; Steven Fernandez, New York City Department of Health and Mental Hygiene; Stephen Immerwahr , New York City Department of Health and Mental Hygiene; Stas Kolenikov, NORC; Amber Levanon Seligson, New York City Department of Health and Mental Hygiene; Martha McRoy, Abt Associates; John Sokolowski, Abt Associates; Nicholas Ruther, Abt Associates; Stephanie Zimmer, Abt Associates
Keywords: ABS Design; Bridge Study; Mode Change; Mode Effect; Splicing Trends; Health Survey
Transitions from Single to Multi-Mode Surveys: The NORC Experience
—Ned English, NORC at the University of Chicago; Anna Wiencrot, NORC at the University of Chicago; Colm O'Muircheartaigh, NORC at the University of Chicago
Keywords: ABS; multi-mode; survey methodology
Combining Data from Probability and Nonprobability Samples Using Doubly Robust Methods
—Michael Elliott, University of Michigan; Ali Rafei, Meta; Carol Flannagan, University of Michigan
Keywords: Non-probability sample; double robustness; augmented inverse propensity weighting
Assessing the Accuracy of Estimates from a Blended Sample Where the Nonprobability Subsample Has Been Calibrated to the Probability Subsample
—Jamie Ridenhour, RTI International; Phillip S. Kott, RTI International
Keywords: selection model; logit function; WTADJX; selection bias; empirical bias; empirical mean squared error
Hybrid Methods for Combining Probability and Nonprobability Samples for Estimation
—Michael Yang, NORC at the University of Chicago; Nada M Ganesh, NORC at the University of Chicago; Edward Mulrow, NORC at the University of Chicago; Evan Herring-Nathan, NORC at the University of Chicago; Vicki Pineau, NORC at the University of Chicago
Keywords: nonprobability sample estimation; statistical matching; propensity weighting; small area estimation; variance estimation
A Dual-Frame Estimation Approach for Combining Probability and Nonprobability Samples
—Chien-Min Huang, Colorado State University; Jay Breidt, NORC at the University of Chicago
Keywords: convenience sample; elastic net; inverse weighted estimator; propensity model; sample matching; variance estimation
Predictive Modeling Using an Enhanced Address-Based
Sampling Frame
—Rachel Harter, RTI International;
Joseph McMichael, RTI International
Keywords: Address-Based Sampling, ABS, frame, auxiliary data, stratification,
predictive modeling
On the Use of Auxiliary Data in Multiple-Source Extensions of Adaptive Survey Design Concepts and Methods (View Presentation)
—Kayla Varela, US Census Bureau; Stephanie Coffey, US Census Bureau; John L. Eltinge, U.S. Census Bureau; Jaya Damineni, US Census Bureau; Anup Mathur, US Census Bureau
Keywords: optimization; agile processes; web-sourced data; administrative records; production systems; adaptive survey design
Tackling the Overabundance of Options in Survey Estimation
—Kelly McConville, Harvard University; Grayson White, RedCastle Resources, Inc.; Olek Wojcik, Reed College; Samuel Olson, Reed College; Paul Nguyen, Reed College; Gretchen Moisen, USDA Forest Service; Tracey Frescino, USDA Forest Service
Keywords: model-assisted estimation; domain estimation; small area estimation; forest inventory; generalized regression estimator; hierarchical bayes
An Approximate Bayesian Approach to Improving Probability Sample Estimators Using a Supplementary Nonprobability Sample
—Yong You, Statistics Canada; Abel DaSylva, Statistics Canada; Jean-Francois Beaumont, Statistics Canada
Keywords: Bayesian prediction; Informative sampling; Non-ignorable sampling; Statistical data integration
Nonresponse Weight Adjustment in the Census Bureau's Probability and Nonprobability Tracking Surveys
—Eric Slud, US Census Bureau
Keywords: design-based; calibration; missing data; large-sample theory; large weight movements; benchmarks
Results from a Stakeholder Feedback Survey for the NCSES Secure Data Access Facility
—Darius Singpurwalla, National Center for Science and Engineering Statistics
Keywords: dissemination; restricted use data; privacy; confidentiality; virtual environment; data access
The National Center for Health Statistics Virtual Data Enclave (VDE)
—J. Neil Russell, National Center for Health Statistics (NCHS)
Keywords: Remote Access; Access to Restricted-use Data; Virtual Data Enclave; CIPSEA; National Center for Health Statistics; Physical Data Enclave
Federal Statistical Research Data Centers Virtual Access
—J. Neil Russell, National Center for Health Statistics (NCHS)
Implementing the Evidence Act’s Standard Application Process
—Spiro Stefanou, USDA-Economic Research Service
Keywords: Evidence Act; Standard Application Process
The Impact of Questionnaire Mode on Estimates of
Health Insurance Coverage and Vaccines for Children Program Eligibility in the National Immunization Survey
—Rachel Francis, NORC at the University of Chicago;
Zachary H. Seeskin, NORC at the University of Chicago;
Amie Conley, NORC at the University of Chicago;
Laurie D. Elam-Evans, National Center for Immunization and Respiratory Diseases;
Chalanda Smith, National Center for Immunization and Respiratory Diseases;
Holly A. Hill, National Center for Immunization and Respiratory Diseases;
Michael Chen, National Center for Immunization and Respiratory Diseases
Keywords: Address-Based Sampling, Mode Effects, Health Insurance, Vaccines for Children Program
Anybody Home? In-Person Recruitment in a Multimode
Design on the MCBS
—Alanah Raykovich, NORC at the University of Chicago;
Holly Hagerty, NORC at the University of Chicago;
Rachel Carnahan, NORC at the University of Chicago;
Jennifer Vanicek, NORC at the University of Chicago
Keywords: survey mode, mode analysis, in-person recruitment, telephone recruitment, gaining cooperation, COVID-19
Total Survey Error Analysis: National Immunization
Survey Adult COVID Module COVID-19 Vaccination Coverage Estimates
—Elizabeth Allen, NORC at the University of Chicago;
Vicki Pineau, NORC at the University of Chicago;
Kirk Wolter, NORC at the University of Chicago;
Jason Boim, NORC at the University of Chicago;
James A. Singleton, National Center for Immunization and Respiratory Diseases;
Michael Chen, National Center for Immunization and Respiratory Diseases;
David Yankey, National Center for Immunization and Respiratory Diseases;
Jennifer Kriss, National Center for Immunization and Respiratory Diseases;
Yi Mu, National Center for Immunization and Respiratory Diseases
Keywords: COVID-19 Vaccination Coverage; Total Survey Error
Impact of Differential Appeals in an Advance Letter Mailing
on Phone Recruitment for a Longitudinal Survey
—Melissa Heim Viox, NORC at the University of Chicago;
Chrystine Tadler, NORC at the University of Chicago;
Megan Bjorgo, NORC at the University of Chicago
Keywords: respondent recruitment, respondent outreach, telephone interviewing, advance letter, experiment
Address-Based Sampling for Socio-Demographic Studies of
the U.S. Jewish Community
—Zachary H. Seeskin, NORC at the University of Chicago;
David Dutwin, NORC at the University of Chicago;
Leonard Saxe, NORC at the University of Chicago
Keywords: Rare populations; hard-to-reach populations; multiple sampling frames; predictive modeling
COVID-19 Vaccination Coverage in the U.S.: Comparison
among National Probability-Based Surveys – National
Immunization Survey Adult COVID Module, Household
Pulse Survey, and the AmeriSpeak® Panel
—Vicki J. Pineau, NORC at the University of Chicago;
Jason Fields, U.S. Bureau of the Census;
James A. Singleton, National Center for Immunization and Respiratory Diseases;
Elizabeth Allen, NORC at the University of Chicago;
David Dutwin;
Sarah Kornylo, NORC at the University of Chicago;
Xiuli Tang, NORC at the University of Chicago;
Michael Chen, National Center for Immunization and Respiratory Diseases;
Benjamin Fredua, National Center for Immunization and Respiratory Diseases
Keywords: COVID-19 Vaccination Coverage; CDC COVID Data Tracker; Nonsampling Error
Multilingual Communities Require Multilingual Surveys:
A Language Justice-Informed Approach to the New York
City Housing and Vacancy Survey
—Caitlin R Waickman, New York City Department of Housing Preservation and Development
Allison Corbett, New York City Department of Housing Preservation and Development
Keywords: Language Justice, Data Collection, Multilingual, Translation
Making Lotteries Legible: Designing Natural Experiments
—Daniel Goldstein, NYC Department of Housing;
Elyzabeth Gaumer, NYC Department of Housing
Keywords: Randomized control trial, natural experiment, quasi-experimental, lottery