Publications

Andrew M. Guess, Dominique Lockett, Benjamin Lyons, Jacob M. Montgomery, Brendan Nyhan, Jason Reifler (2020). Fake news may have limited effects beyond increasing beliefs in false claims. Harvard Kennedy School Misinformation Review, 1(1).

Florian Hollenbach, Jacob M. Montgomery (2020). Bayesian Model Selection, Model Comparison, and Model Averaging. SAGE Handbook of Research Methods in Political Science and International Relations.

Andrew M. Guess, Michael Lerner, Benjamin Lyons, Jacob M. Montgomery, Brendan Nyhan, Jason Reifler, Neelanjan Sircar (2020). A Digital Media Literacy Intervention Increases Discernment Between Mainstream and False News in the United States and India. Proceedings of the National Academy of Sciences, 117(27), 15536-15545.

Patrick D. Tucker, Jacob M. Montgomery, Steven S. Smith (2019). Party Identification in the Age of Obama: Evidence on the Sources of Stability and Systematic Change in Party Identification from a Long-Term Panel Survey. Political Research Quarterly, 72(2), 309-328.

Florian Hollenbach, Jacob M. Montgomery, Adriana Crespo-Tenorio (2019). Bayesian Versus Maximum Likelihood Estimation of Treatment Effects in Bivariate Probit Instrumental Variable Models. Political Science Research and Methods, 7(3), 651-659.

Jacob M. Montgomery, Santiago Olivella (2018). Tree-Based Models for Political Science Data. American Journal of Political Science, 62(3), 729-744.

Ryden Butler, Brendan Nyhan, Jacob M. Montgomery, Michelle Torres (2018). Revisiting White Backlash: How Race Affects Death Penalty Opinion Today. Research and Politics, 5(1).

Jacob M. Montgomery, Brendan Nyhan, Michelle Torres (2018). How Conditioning on Post-Treatment Variables Can Ruin Your Experiment and What to Do About It. American Journal of Political Science, 62(3), 760-775.

Jacob M. Montgomery, Brendan Nyhan (2017). The Effects of Congressional Staff Networks in the U.S. House of Representatives. Journal of Politics, 79(3), 745-761.

David Carlson, Jacob M. Montgomery (2017). A Pairwise Comparison Framework for Fast, Flexible, and Reliable Human Coding of Political Texts. American Political Science Review, 111(4), 835-843.