Matthew Tyler

I am an Assistant Professor in the Department of Political Science at Rice University. I develop and apply statistical methods to study public opinion and political behavior, with a focus on measurement, causal inference, and partisan polarization.

Most of my current research examines how errors in survey responses affect what we can learn about political attitudes. I am the principal investigator on a National Science Foundation (NSF) CAREER grant supporting the development of methods to address these errors, with applications to measuring support for political violence and belief in conspiracy theories.

I earned my PhD in Political Science from Stanford University in 2021 and hold bachelor’s degrees in Statistical Science and Mathematics from Duke University.

Peer Reviewed Articles

  1. Campaigns Reinforce Partisanship and Short-Term Forces: Evidence from a Large-Scale Panel Study of the 2020 US Presidential Campaign

    Tyler, Matthew, Shanto Iyengar, Arjun Wilkins, et al.

    Political Science Research and Methods. Conditionally accepted (pending replication).

  2. Why Are Surveys Struggling to Estimate Vote Shares?

    Tyler, Matthew, D. Sunshine Hillygus, Matthew DeBell, Ted Brader, Shanto Iyengar, Daron Shaw, and Nicholas Valentino.

    American Journal of Political Science (Early View).

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  3. Evaluating a New Generation of Expansive Claims about Vote Manipulation

    Grimmer, Justin, Michael C. Herron, and Matthew Tyler. 2024.

    Election Law Journal 23(3): 211–236.

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  4. Testing the Robustness of the ANES Feeling Thermometer Indicators of Affective Polarization

    Tyler, Matthew, and Shanto Iyengar. 2024.

    American Political Science Review 118(3): 1570–1576.

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  5. Learning to Dislike Your Opponents: Political Socialization in the Era of Polarization

    Tyler, Matthew, and Shanto Iyengar. 2023.

    American Political Science Review 117(1): 347–354.

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  6. Current Research Overstates American Support for Political Violence

    Westwood, Sean J., Justin Grimmer, Matthew Tyler, and Clayton Nall. 2022.

    Proceedings of the National Academy of Sciences 119(12): e2116870119.

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  7. Partisan Enclaves and Information Bazaars: Mapping Selective Exposure to Online News

    Tyler, Matthew, Justin Grimmer, and Shanto Iyengar. 2022.

    The Journal of Politics 84(2): 1057–1073.

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  8. The Structure of Political Choices: Distinguishing Between Constraint and Multidimensionality

    Marble, William, and Matthew Tyler. 2022.

    Political Analysis 30(3): 328–345.

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  9. Machine Learning Predictions as Regression Covariates

    Fong, Christian, and Matthew Tyler. 2021.

    Political Analysis 29(4): 467–484.

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Working papers

  • A Statistical Framework to Engage the Problem of Disengaged Survey Respondents: Measuring Public Support for Partisan Violence

    Tyler, Matthew, Justin Grimmer, and Sean Westwood.

    Working paper, July 13, 2024.

    SSRN

  • Designing for Power: Covariates, Indices, and Efficiency in Survey Experiments

    Erik Peterson, Matthew Tyler, and Agustin Prinetti.

    Working paper, January 14, 2026.

    SSRN

  • Bounding Causal Effects in Survey Experiments with Noncompliance or Inattention

    Tyler, Matthew.

    Working paper.

    PDF

Other Publications

  1. Reply to Kalmoe and Mason: The Pitfalls of Using Surveys to Measure Low-Prevalence Attitudes and Behavior

    Westwood, Sean J., Justin Grimmer, Matthew Tyler, and Clayton Nall. 2022.

    Proceedings of the National Academy of Sciences 119(32): e2207584119.

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