66 citations · 189 across the 22 of their papers we have counts for
21 papers · 1 filter
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…
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…
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…
Bayesian Mixture Models With Focused Clustering for Mixed Ordinal and Nominal Data
Maria DeYoreo, Jerome P. Reiter, D. Sunshine Hillygus
In some contexts, mixture models can fit certain variables well at the expense of others in ways beyond the analyst's control. For example, when the data include some variables wit…
Categorical Data Fusion Using Auxiliary Information
Bailey K. Fosdick, Maria DeYoreo, Jerome P. Reiter
In data fusion analysts seek to combine information from two databases comprised of disjoint sets of individuals, in which some variables appear in both databases and other variabl…
Dirichlet Process Mixture Models for Modeling and Generating Synthetic Versions of Nested Categorical Data
Jingchen Hu, Jerome P. Reiter, Quanli Wang
We present a Bayesian model for estimating the joint distribution of multivariate categorical data when units are nested within groups. Such data arise frequently in social science…
Bayesian Marked Point Process Modeling for Generating Fully Synthetic Public Use Data with Point-Referenced Geography
Harrison Quick, Scott H. Holan, Christopher K. Wikle +1
Many data stewards collect confidential data that include fine geography. When sharing these data with others, data stewards strive to disseminate data that are informative for a w…