116 citations · 155 across the 16 of their papers we have counts for
16 papers
Statistical Assessments of Representational Reforms: A Case Study from Los Angeles
Sarah Cannon, Evan T. R. Rosenman
Electoral reforms -- including changes to district boundaries, electoral rules, and the size of elected bodies -- are a recurrent feature of American state and municipal politics.…
Bayesian Uncertainty Quantification for Ranked Choice Voting Polls
Evan T. R. Rosenman, Jason Liang
Ranked choice voting (RCV) is a popular alternative voting method in which voters are asked to list their favored candidates in preference order, rather than vote for a single cand…
Adaptive Experimental Design Using Shrinkage Estimators
Evan T. R. Rosenman, Kristen B. Hunter
In multi-armed trials, adaptive designs are a popular way to increase estimation efficiency or identify optimal treatments. Several recent papers have proposed adaptive variants of…
Empirical Bayes Double Shrinkage for Combining Biased and Unbiased Causal Estimates
Evan T. R. Rosenman, Francesca Dominici, Luke Miratrix
Motivated by the proliferation of observational datasets and the need to integrate non-randomized evidence with randomized controlled trials, causal inference researchers have rece…
Comment: The Essential Role of Policy Evaluation for the 2020 Census Disclosure Avoidance System
Christopher T. Kenny, Shiro Kuriwaki, Cory McCartan +3
In "Differential Perspectives: Epistemic Disconnects Surrounding the US Census Bureau's Use of Differential Privacy," boyd and Sarathy argue that empirical evaluations of the Censu…
Race and ethnicity data for first, middle, and last names
Evan T. R. Rosenman, Santiago Olivella, Kosuke Imai
We provide the largest compiled publicly available dictionaries of first, middle, and last names for the purpose of imputing race and ethnicity using, for example, Bayesian Improve…
Addressing Census data problems in race imputation via fully Bayesian Improved Surname Geocoding and name supplements
Kosuke Imai, Santiago Olivella, Evan T. R. Rosenman
Prediction of individual's race and ethnicity plays an important role in social science and public health research. Examples include studies of racial disparity in health and votin…
Designing Experiments Toward Shrinkage Estimation
Evan T. R. Rosenman, Luke Miratrix
We consider how increasingly available observational data can be used to improve the design of randomized controlled trials (RCTs). We seek to design a prospective RCT, with the in…
Recalibration of Predictive Models as Approximate Probabilistic Updates
Evan T. R. Rosenman, Santiago Olivella
The output of predictive models is routinely recalibrated by reconciling low-level predictions with known derived quantities defined at higher levels of aggregation. For example, m…
Robust Designs for Prospective Randomized Trials Surveying Sensitive Topics
Evan T. R. Rosenman, Rina Friedberg, Mike Baiocchi
We consider the problem of designing a prospective randomized trial in which the outcome data will be self-reported, and will involve sensitive topics. Our interest is in misreport…
The Impact of the U.S. Census Disclosure Avoidance System on Redistricting and Voting Rights Analysis
Christopher T. Kenny, Shiro Kuriwaki, Cory McCartan +3
The US Census Bureau plans to protect the privacy of 2020 Census respondents through its Disclosure Avoidance System (DAS), which attempts to achieve differential privacy guarantee…
Designing Experiments Informed by Observational Studies
Evan Rosenman, Art B. Owen
The increasing availability of passively observed data has yielded a growing methodological interest in "data fusion." These methods involve merging data from observational and exp…
Combining Observational and Experimental Datasets Using Shrinkage Estimators
Evan Rosenman, Guillaume Basse, Art Owen +1
We consider the problem of combining data from observational and experimental sources to make causal conclusions. This problem is increasingly relevant, as the modern era has yield…
Some New Results for Poisson Binomial Models
Evan Rosenman
We consider a problem of ecological inference, in which individual-level covariates are known, but labeled data is available only at the aggregate level. The intended application i…
Propensity Score Methods for Merging Observational and Experimental Datasets
Evan Rosenman, Art B. Owen, Michael Baiocchi +1
This project considers how one might augment a limited amount of data from randomized controlled trial (RCT) with more plentiful data from an observational database (ODB), in order…
Using Poisson Binomial GLMs to Reveal Voter Preferences
Evan Rosenman, Nitin Viswanathan
We present a new modeling technique for solving the problem of ecological inference, in which individual-level associations are inferred from labeled data available only at the agg…