Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records (Supplementary Appendix, Simulations Appendix), with Ted Enamorado and Kosuke Imai. Forthcoming, American Political Science Review. 

Working Papers:

A New Automated Redistricting Simulator Using Markov Chain Monte Carlo, with Michael Higgins, Kosuke Imai, and Alexander Tarr. Under Review. 

Improving Model-Building Workflows for Predicting Heterogeneous Treatment Effects

Validating Ensembles of Simulated Redistricting Plans

fastLink: R Package for Fast Probabilistic Record Linkage, with Ted Enamorado and Kosuke Imai

Other Writings:

User’s Guide and Codebook for the ANES 2016 Time Series Voter Validation Supplemental Data, with Ted Enamorado and Kosuke Imai