Contributed Papers

Weighting, variance estimation, and modeling

Wed, Aug 6, 2:00 PM - 3:50 PM Room CC-Davidson Ballroom A2 Music City Center

Xin WangChair

Survey Research Methods Section

6 Presentations

Moving toward best practice when using propensity score weighting in survey observational studies

2:05 PM - 2:20 PM

Co-authors: Guangyu Tong (Yale University), Fan Li (Yale School of Public Health), Guangyu Tong (Yale University), Yukang Zeng (Yale)

complex survey propensity score weighting survey weights overlap weights

Sample-split regression estimation with high dimensional covariates in survey sampling

2:20 PM - 2:35 PM

Co-authors: Yonghyun Kwon (Korea Military Academy), Jae-Kwang Kim (Iowa State University), Yonghyun Kwon (Korea Military Academy), Shu Yang (North Carolina State University, Department of Statistics)

Sample-split estimation Informative sampling Model-assisted estimation High-dimensional regression

Enhancing Iterative Proportional Fitting for Efficient and Scalable Synthetic Population Generation

2:35 PM - 2:50 PM

Co-authors: William Agyapong (University of Texas At El Paso), William Agyapong (University of Texas At El Paso), Amy Wagler (University of Texas At El Paso)

Iterative Proportional Fitting (IPF), block-wise IPF, synthetic population generation, high-dimensional data, contingency tables, marginal constraints, scalability Zero-cell-issues, computational efficiency, survey weighting, generative models, Bayesian networks, tabular variational autoencoders (TVAEs)

WITHDRAW: Spatio-temporal Bayesian modeling for estimating CPIs in small domains´

2:50 PM - 3:05 PM

Co-authors: Vladislav Beresovsky (U.S. Bureau of Labor Statistics), Vladislav Beresovsky (U.S. Bureau of Labor Statistics), Terrance Savitsky (US Bureau of Labor Statistics)

small area estimation hierarchical Bayesian models spatio-temporal correlations STAN Gaussian processes

Optimal Use of Survey Weights for Causal Inference under Informative Sampling

3:05 PM - 3:20 PM

Co-authors: Shubhajit Sen, Shu Yang (North Carolina State University, Department of Statistics), Shubhajit Sen

Complex survey Data-Adaptive Method Doubly Robust Estimation Empirical process Population average treatment effect

Testing interaction effects with weighted interval-censoring Cox proportional hazard models

3:20 PM - 3:35 PM

Co-authors: Adriana Perez (University of Texas At Houston, Health Science Center), Sarah Valencia (Michael and Susan Dell Center for Healthy Living), Adriana Perez (University of Texas At Houston, Health Science Center)

Sampling weights Fay's variance estimation Balanced Repeated Replicate Weights Interval-Censoring Hazard Function hazard risk age of onset