Matthew Tyler

About Me

I am a postdoc for both the Democracy and Polarization Lab and American National Election Studies (ANES) at Stanford University. Broadly, my research focuses on political methodology, partisan polarization, and political media. Specifically, I develop new statistical tools and techniques to measure the nature, causes, and consequences of political polarization in American politics. My research is published or forthcoming at Proceedings of the National Academy of Sciences, American Political Science Review, The Journal of Politics, and Political Analysis.

Link to my C.V.

Publications

1. Learning to Dislike Your Opponents: Political Socialization in the Era of Polarization”
   with Shanto Iyengar.
   Forthcoming, American Political Science Review

2. Current Research Overstates American Support for Political Violence
   with Sean Westwood, Justin Grimmer, and Clayton Nall
   2022, Proceedings of the National Academy of Sciences
   
   • See also Reply to Kalmoe and Mason: The pitfalls of using surveys to measure low-prevalence attitudes and behavior with Sean Westwood, Justin Grimmer, and Clayton Nall. 2022, Proceedings of the National Academy of Sciences

3. Partisan Enclaves and Information Bazaars: Mapping Selective Exposure to Online News
   with Justin Grimmer and Shanto Iyengar
   2022, The Journal of Politics

4. The Structure of Political Choices: Distinguishing Between Constraint and Multidimensionality
   with William Marble
   2022, Political Analysis

5. Machine Learning Predictions as Regression Covariates
   with Christian Fong
   2021, Political Analysis

Working Papers

• Counterfactual Forecasting: Causal Inference without Simultaneous Controls

• Evaluating a New Generation of Expansive Claims about Vote Manipulation
  with Justin Grimmer, Michael C. Herron

• A Statistical Framework to Engage the Problem of Disengaged Survey Respondents
  with Justin Grimmer, Sean Westwood

• Testing the Robustness of the ANES Feeling Thermometer Indicators of Affective Polarization
  with Shanto Iyengar

• Getting More out of Human Coders with Statistical Models

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