Using Statistics to Determine Causal Relationships. - Jerome P. Reiter (Am. Math. Mon., 2000)

Model Diagnostics for Remote Access Regression Servers. - Jerome P. Reiter (Stat. Comput., 2003)

Regression on Distributed Databases via Secure Multi-Party Computation. - Alan F. Karr; Xiaodong Lin 004; Ashish P. Sanil; Jerome P. Reiter (DG.O, 2004)

Privacy preserving regression modelling via distributed computation. - Ashish P. Sanil; Alan F. Karr; Xiaodong Lin 004; Jerome P. Reiter (KDD, 2004)

Secure analysis of distributed chemical databases without data integration. - Alan F. Karr; Jun Feng; Xiaodong Lin 004; Ashish P. Sanil; S. Stanley Young; Jerome P. Reiter (J. Comput. Aided Mol. Des., 2005)

Adjusting Survey Weights When Altering Identifying Design Variables Via Synthetic Data. - Robin Mitra; Jerome P. Reiter (Privacy in Statistical Databases, 2006)

Secure computation with horizontally partitioned data using adaptive regression splines. - Joyee Ghosh; Jerome P. Reiter; Alan F. Karr (Comput. Stat. Data Anal., 2007)

Secure, Privacy-Preserving Analysis of Distributed Databases. - Alan F. Karr; William J. Fulp; Francisco Vera; S. Stanley Young; Xiaodong Lin 004; Jerome P. Reiter (Technometrics, 2007)

Accounting for Intruder Uncertainty Due to Sampling When Estimating Identification Disclosure Risks in Partially Synthetic Data. - Jörg Drechsler; Jerome P. Reiter (Privacy in Statistical Databases, 2008)

Verification servers: Enabling analysts to assess the quality of inferences from public use data. - Jerome P. Reiter; Anna Oganian; Alan F. Karr (Comput. Stat. Data Anal., 2009)

Estimating Risks of Identification Disclosure in Partially Synthetic Data. - Jerome P. Reiter; Robin Mitra (J. Priv. Confidentiality, 2009)

Global Measures of Data Utility for Microdata Masked for Disclosure Limitation. - Mi-Ja Woo; Jerome P. Reiter; Anna Oganian; Alan F. Karr (J. Priv. Confidentiality, 2009)

Multiple Imputation for Disclosure Limitation: Future Research Challenges. - Jerome P. Reiter (J. Priv. Confidentiality, 2010)

Random Forests for Generating Partially Synthetic, Categorical Data. - Gregory Caiola; Jerome P. Reiter (Trans. Data Priv., 2010)

An empirical evaluation of easily implemented, nonparametric methods for generating synthetic datasets. - Jörg Drechsler; Jerome P. Reiter (Comput. Stat. Data Anal., 2011)

Model Selection when multiple imputation is used to protect confidentiality in public use data. - Satkartar K. Kinney; Jerome P. Reiter; James O. Berger (J. Priv. Confidentiality, 2011)

Comment on Article by Gates. - Jerome P. Reiter (J. Priv. Confidentiality, 2011)

Statistical Approaches to Protecting Confidentiality in Public Use Data. - Jerome P. Reiter (International Encyclopedia of Statistical Science, 2011)

Big privacy: protecting confidentiality in big data. - Ashwin Machanavajjhala; Jerome P. Reiter (XRDS, 2012)

Towards Providing Automated Feedback on the Quality of Inferences from Synthetic Datasets. - David McClure 003; Jerome P. Reiter (J. Priv. Confidentiality, 2012)

Differential Privacy and Statistical Disclosure Risk Measures: An Investigation with Binary Synthetic Data. - David McClure 003; Jerome P. Reiter (Trans. Data Priv., 2012)

Secure Bayesian model averaging for horizontally partitioned data. - Joyee Ghosh; Jerome P. Reiter (Stat. Comput., 2013)

Disclosure Risk Evaluation for Fully Synthetic Categorical Data. - Jingchen Hu; Jerome P. Reiter; Quanli Wang (Privacy in Statistical Databases, 2014)

Bayesian Estimation of Disclosure Risks for Multiply Imputed, Synthetic Data. - Jerome P. Reiter; Quanli Wang; Biyuan Zhang (J. Priv. Confidentiality, 2014)

Differentially Private Regression Diagnostics. - Yan Chen 022; Ashwin Machanavajjhala; Jerome P. Reiter; Andrés F. Barrientos (ICDM, 2016)

Privacy-Preserving Data Analysis for the Federal Statistical Agencies. - John M. Abowd; Lorenzo Alvisi; Cynthia Dwork; Sampath Kannan; Ashwin Machanavajjhala; Jerome P. Reiter (CoRR, 2017)

Differentially private posterior summaries for linear regression coefficients. - Gilad Amitai; Jerome P. Reiter (J. Priv. Confidentiality, 2018)

Reminiscences of Steve Fienberg. - Jerome P. Reiter (J. Priv. Confidentiality, 2018)

Is my model any good: differentially private regression diagnostics. - Yan Chen 022; Andrés F. Barrientos; Ashwin Machanavajjhala; Jerome P. Reiter (Knowl. Inf. Syst., 2018)

Differentially Private Verification of Regression Predictions from Synthetic Data. - Haoyang Yu; Jerome P. Reiter (Trans. Data Priv., 2018)

Bayesian Modeling for Simultaneous Regression and Record Linkage. - Jiurui Tang; Jerome P. Reiter; Rebecca C. Steorts (PSD, 2020)

Post-processing Differentially Private Counts to Satisfy Additive Constraints. - Ziang Wang; Jerome P. Reiter (Trans. Data Priv., 2021)

A Latent Class Modeling Approach for Differentially Private Synthetic Data for Contingency Tables. - Michelle Nixon; Andrés F. Barrientos; Jerome P. Reiter; Aleksandra B. Slavkovic (J. Priv. Confidentiality, 2022)

An In-Depth Examination of Requirements for Disclosure Risk Assessment. - Ron S. Jarmin; John M. Abowd; Robert Ashmead; Ryan Cumings-Menon; Nathan Goldschlag; Michael B. Hawes; Sallie Ann Keller; Daniel Kifer; Philip Leclerc; Jerome P. Reiter; Rolando A. Rodríguez; Ian M. Schmutte; et al. (CoRR, 2023)

Synthetic Data: A Look Back and A Look Forward. - Jerome P. Reiter (Trans. Data Priv., 2023)

ER-Evaluation: End-to-End Evaluation of Entity Resolution Systems. - Olivier Binette; Jerome P. Reiter (J. Open Source Softw., 2023)

Prior-itizing Privacy: A Bayesian Approach to Setting the Privacy Budget in Differential Privacy. - Zeki Kazan; Jerome P. Reiter (NeurIPS, 2024)

How to Evaluate Entity Resolution Systems: An Entity-Centric Framework with Application to Inventor Name Disambiguation. - Olivier Binette; Youngsoo Baek; Siddharth Engineer; Christina Jones; Abel Dasylva; Jerome P. Reiter (CoRR, 2024)

Bayesian Inference Under Differential Privacy: Prior Selection Considerations with Application to Univariate Gaussian Data and Regression. - Zeki Kazan; Jerome P. Reiter (CoRR, 2024)

Improving the Validity and Practical Usefulness of AI/ML Evaluations Using an Estimands Framework. - Olivier Binette; Jerome P. Reiter (CoRR, 2024)

Differentially Private Finite Population Estimation via Survey Weight Regularization. - Jeremy Seeman; Yajuan Si; Jerome P. Reiter (CoRR, 2024)

Launching the Society for Privacy and Confidentiality Research to Own the Journal of Privacy and Confidentiality. - John M. Abowd; Cynthia Dwork; Alan F. Karr; Kobbi Nissim; Jerome P. Reiter; Aleksandra B. Slavkovic; Lars Vilhuber (J. Priv. Confidentiality, 2024)

Differentially private estimation of weighted average treatment effects for binary outcomes. - Sharmistha Guha; Jerome P. Reiter (Comput. Stat. Data Anal., 2025)

Changes to the Journal of Privacy and Confidentiality. - John M. Abowd; Cynthia Dwork; Alan F. Karr; Jerome P. Reiter; Aleksandra B. Slavkovic (J. Priv. Confidentiality, 2025)

Differentially Private Verification of Survey-Weighted Estimates. - Tong Lin; Jerome P. Reiter (Trans. Data Priv., 2025)

Optimal F-score Matching for Bipartite Record Linkage. - Eric A. Bai; Olivier Binette; Jerome P. Reiter (Stat. Comput., 2025)