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Sensitivity Analysis for Survey Weights

Survey weighting allows researchers to account for bias in survey samples, due to unit nonresponse or convenience sampling, using measured demographic covariates. Unfortunately, in practice, it is impossible...

Leveraging Population Outcomes to Improve the Generalization of Experimental Results

Generalizing causal estimates in randomized experiments to a broader target population is essential for guiding decisions by policymakers and practitioners in the social and biomedical sciences. While recent papers developed various weighting estimators for the population average treatment effect (PATE), many of these methods result in large variance because the experimental sample...

Multilevel calibration weighting for survey data

A pressing challenge in modern survey research is to find calibration weights when covariates are high dimensional and especially when interactions between variables are important...

A kernel balancing approach for reducing specification assumptions in survey weighting

Response rates to surveys have declined precipitously. Some researchers have responded by relying more heavily on convenience-based internet samples. This leaves researchers asking...

Statistical Advances in Post-Election Ballot Auditing

Post-election audits are an integral part of the broader election audit process. Depending on the auditing method, they may detect miscounts in the official tabulation of votes, or limit the risk of certifying an incorrect outcome...

Target Selection as Variable Selection: Using the Lasso to Select Auxiliary Vectors for the Construction of Survey Weights

Survey nonresponse is a ubiquitous problem in modern survey research. As individuals have become less likely to respond to surveys there has been a simultaneous rise in highly granular data sources...