6 papers
Differentially Private Bayesian Inference for Gaussian Copula Correlations
Shuo Wang, Joseph Feldman, Jerome P. Reiter
Gaussian copulas are widely used to estimate multivariate distributions and relationships. We present algorithms for estimating Gaussian copula correlations that ensure differentia…
Differentially Private Computation of the Gini Index for Income Inequality
Wenjie Lan, Jerome P. Reiter
The Gini index is a widely reported measure of income inequality. In some settings, the underlying data used to compute the Gini index are confidential. The organization charged wi…
Outcome-Assisted Multiple Imputation of Missing Treatments
Joseph Feldman, Jerome P. Reiter
We provide guidance on multiple imputation of missing at random treatments in observational studies. Specifically, analysts should account for both covariates and outcomes, i.e., n…
Multiple imputation for nonresponse in surveys using design weights and auxiliary margins
Kewei Xu, Jerome P. Reiter
Survey data typically have missing values due to unit and item nonresponse. Sometimes, survey organizations know the marginal distributions of certain categorical variables in the…
Imputation of Nonignorable Missing Data in Surveys Using Auxiliary Margins Via Hot Deck and Sequential Imputation
Yanjiao Yang, Jerome P. Reiter
Survey data collection often is plagued by unit and item nonresponse. To reduce reliance on strong assumptions about the missingness mechanisms, statisticians can use information a…
Gaussian Copula Models for Nonignorable Missing Data Using Auxiliary Marginal Quantiles
Joseph Feldman, Jerome P. Reiter, Daniel R. Kowal
We present an approach for modeling and imputation of nonignorable missing data. Our approach uses Bayesian data integration to combine (1) a Gaussian copula model for all study va…