Using a Probabilistic Model to Assist Merging of Large-scale Administrative Records (Supplementary Appendix, Simulations Appendix), with Ted Enamorado and Kosuke Imai (2019). American Political Science Review, Vol. 113, No. 2 (May), pp. 353-371.

Working Papers:

A New Automated Redistricting Simulator Using Markov Chain Monte Carlo, with Michael Higgins, Kosuke Imai, and Alexander Tarr. Revise & Resubmit, Journal of Computational and Graphical Statistics.

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 Writing:

Empirical and Computational Methods for Electoral Politics (2018). PhD Thesis, Department of Politics, Princeton University.

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