66 citations · 189 across the 22 of their papers we have counts for
30 papers
Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy
Zeki Kazan, Jerome P. Reiter
When releasing outputs from confidential data, agencies need to balance the analytical usefulness of the released data with the obligation to protect data subjects' confidentiality…
A Generator for Generalized Inverse Gaussian Distributions
Xiaozhu Zhang, Jerome P. Reiter
We propose a new generator for the generalized inverse Gaussian (GIG) distribution by decomposing the density of GIG into two components. The first component is a truncated inverse…
Using auxiliary marginal distributions in imputations for nonresponse while accounting for survey weights, with application to estimating voter turnout
Jiurui Tang, D. Sunshine Hillygus, Jerome P. Reiter
The Current Population Survey is the gold-standard data source for studying who turns out to vote in elections. However, it suffers from potentially nonignorable unit and item nonr…
Assessing Statistical Disclosure Risk for Differentially Private, Hierarchical Count Data, with Application to the 2020 U.S. Decennial Census
Zeki Kazan, Jerome Reiter
We propose Bayesian methods to assess the statistical disclosure risk of data released under zero-concentrated differential privacy, focusing on settings with a strong hierarchical…
A Latent Class Modeling Approach for Generating Synthetic Data and Making Posterior Inferences from Differentially Private Counts
Michelle Pistner Nixon, Andrés F. Barrientos, Jerome P. Reiter +1
Several algorithms exist for creating differentially private counts from contingency tables, such as two-way or three-way marginal counts. The resulting noisy counts generally do n…
Differentially Private Methods for Releasing Results of Stability Analyses
Chengxin Yang, Jerome P. Reiter
Data stewards and analysts can promote transparent and trustworthy science and policy-making by facilitating assessments of the sensitivity of published results to alternate analys…
Multiple Imputation for Nonignorable Item Nonresponse in Complex Surveys Using Auxiliary Margin
Olanrewaju Akande, Jerome P. Reiter
We outline a framework for multiple imputation of nonignorable item nonresponse when the marginal distributions of some of the variables with missing values are known. In particula…
Bayesian Causal Inference with Bipartite Record Linkage
Sharmistha Guha, Jerome P. Reiter, Andrea Mercatanti
In many scenarios, the observational data needed for causal inferences are spread over two data files. In particular, we consider scenarios where one file includes covariates and t…
Leveraging Random Assignment to Impute Missing Covariates in Causal Studies
Gauri Kamat, Jerome P. Reiter
Baseline covariates in randomized experiments are often used in the estimation of treatment effects, for example, when estimating treatment effects within covariate-defined subgrou…
Leveraging Auxiliary Information on Marginal Distributions in Nonignorable Models for Item and Unit Nonresponse
Olanrewaju Akande, Gabriel Madson, D. Sunshine Hillygus +1
Often, government agencies and survey organizations know the population counts or percentages for some of the variables in a survey. These may be available from auxiliary sources,…
Sequentially additive nonignorable missing data modeling using auxiliary marginal information
Mauricio Sadinle, Jerome P. Reiter
We study a class of missingness mechanisms, called sequentially additive nonignorable, for modeling multivariate data with item nonresponse. These mechanisms explicitly allow the p…
Simultaneous Edit and Imputation for Household Data with Structural Zeros
Olanrewaju Akande, Andrés Barrientos, Jerome P. Reiter
Multivariate categorical data nested within households often include reported values that fail edit constraints---for example, a participating household reports a child's age as ol…
Simultaneous Record Linkage and Causal Inference with Propensity Score Subclassification
Joan Heck Wortman, Jerome P. Reiter
We develop methodology for causal inference in observational studies when using propensity score subclassification on data constructed with probabilistic record linkage techniques.…
Multiple Imputation of Missing Values in Household Data with Structural Zeros
Olanrewaju Akande, Jerome Reiter, Andrés F. Barrientos
We present an approach for imputation of missing items in multivariate categorical data nested within households. The approach relies on a latent class model that (i) allows for ho…
Differentially private significance tests for regression coefficients
Andrés F. Barrientos, Jerome P. Reiter, Ashwin Machanavajjhala +1
Many data producers seek to provide users access to confidential data without unduly compromising data subjects' privacy and confidentiality. One general strategy is to require use…
Providing Access to Confidential Research Data Through Synthesis and Verification: An Application to Data on Employees of the U.S. Federal Government
Andrés F. Barrientos, Alexander Bolton, Tom Balmat +6
Data stewards seeking to provide access to large-scale social science data face a difficult challenge. They have to share data in ways that protect privacy and confidentiality, are…
Sequential identification of nonignorable missing data mechanisms
Mauricio Sadinle, Jerome P. Reiter
With nonignorable missing data, likelihood-based inference should be based on the joint distribution of the study variables and their missingness indicators. These joint models can…
Privacy-Preserving Data Analysis for the Federal Statistical Agencies
John Abowd, Lorenzo Alvisi, Cynthia Dwork +3
Government statistical agencies collect enormously valuable data on the nation's population and business activities. Wide access to these data enables evidence-based policy making,…
Data Fusion for Correcting Measurement Errors
Tracy Schifeling, Jerome P. Reiter, Maria DeYoreo
Often in surveys, key items are subject to measurement errors. Given just the data, it can be difficult to determine the distribution of this error process, and hence to obtain acc…
Itemwise conditionally independent nonresponse modeling for incomplete multivariate data
Mauricio Sadinle, Jerome P. Reiter
We introduce a nonresponse mechanism for multivariate missing data in which each study variable and its nonresponse indicator are conditionally independent given the remaining vari…
Regression Modeling and File Matching Using Possibly Erroneous Matching Variables
Nicole M. Dalzell, Jerome P. Reiter
Many analyses require linking records from two databases comprising overlapping sets of individuals. In the absence of unique identifiers, the linkage procedure often involves matc…
Bayesian mixture modeling for multivariate conditional distributions
Maria DeYoreo, Jerome P. Reiter
We present a Bayesian mixture model for estimating the joint distribution of mixed ordinal, nominal, and continuous data conditional on a set of fixed variables. The model uses mul…
Stop or Continue Data Collection: A Nonignorable Missing Data Approach for Continuous Variables
Thais Paiva, Jerry Reiter
We present an approach to inform decisions about nonresponse follow-up sampling. The basic idea is (i) to create completed samples by imputing nonrespondents' data under various as…
An Empirical Comparison of Multiple Imputation Methods for Categorical Data
Olanrewaju Akande, Fan Li, Jerome Reiter
Multiple imputation is a common approach for dealing with missing values in statistical databases. The imputer fills in missing values with draws from predictive models estimated f…