Jacob M. Montgomery
Jacob M. Montgomery
Professor of Political Science, Washington University in Saint Louis
Verified email at - Homepage
Cited by
Cited by
How conditioning on post-treatment variables can ruin your experiment and what to do about it
JM Montgomery, B Nyhan, M Torres
A digital media literacy intervention increases discernment between mainstream and false news in the United States and India
AM Guess, M Lerner, B Lyons, JM Montgomery, B Nyhan, J Reifler, ...
Proceedings of the National Academy of Sciences 117 (27), 15536-15545, 2020
Turnout as a Habit
JH Aldrich, JM Montgomery, W Wood
Political Behavior 33 (4), 535-563, 2011
Bayesian Model Averaging: Theoretical developments and practical applications
JM Montgomery, B Nyhan
Political Analysis 18 (2), 245-270, 2010
Improving Predictions Using Ensemble Bayesian Model Averaging
JM Montgomery, F Hollenbach, MD Ward
Political Analysis 20 (3), 271-291, 2012
Tree-based models for political science data
JM Montgomery, S Olivella
The effects of unsubstantiated claims of voter fraud on confidence in elections
N Berlinski, M Doyle, AM Guess, G Levy, B Lyons, JM Montgomery, ...
Journal of Experimental Political Science 10 (1), 34-49, 2023
Overconfidence in news judgments is associated with false news susceptibility
BA Lyons, JM Montgomery, AM Guess, B Nyhan, J Reifler
Proceedings of the National Academy of Sciences 118 (23), 2021
The Effects of Congressional Staff Networks in the US House of Representatives
JM Montgomery, B Nyhan
The Journal of Politics 79 (3), 745-761, 2017
Connecting the candidates: Consultant networks and the diffusion of campaign strategy in American congressional elections
B Nyhan, JM Montgomery
American Journal of Political Science 59 (2), 292-308, 2015
“Fake news” may have limited effects beyond increasing beliefs in false claims
AM Guess, D Lockett, B Lyons, JM Montgomery, B Nyhan, J Reifler
Harvard Kennedy School Misinformation Review 1 (1), 2020
Polarization and Ideology: Partisan Sources of Low Dimensionality in Scaled Roll Call Analyses
JH Aldrich, JM Montgomery, DB Sparks
Political Analysis 22 (4), 435-456, 2014
Topics, Concepts, and Measurement: A Crowdsourced Procedure for Validating Topics as Measures
L Ying, JM Montgomery, BM Stewart
Political Analysis, 1-20, 2021
A pairwise comparison framework for fast, flexible, and reliable human coding of political texts
D Carlson, JM Montgomery
American Political Science Review 111 (4), 835-843, 2017
Computerized Adaptive Testing for Public Opinion Surveys
JM Montgomery, J Cutler
Political Analysis 21 (2), 141-171, 2013
An Informed Forensics Approach to Detecting Vote Irregularities
JM Montgomery, S Olivella, JD Potter, BF Crisp
Political Analysis 23 (4), 488-505, 2015
Fake news, Facebook ads, and misperceptions: Assessing information quality in the 2018 US midterm election campaign
A Guess, B Lyons, JM Montgomery, B Nyhan, J Reifler
Democracy Fund report. www. dartmouth. edu/~ nyhan/fake-news-2018. pdf, 2019
Enforcing the minimum drinking age: state, local and agency characteristics associated with compliance checks and Cops in Shops programs
JM Montgomery, KL Foley, M Wolfson
Addiction 101 (2), 223-231, 2006
Static Stability and Evolving Constraint Preference Stability and Ideological Structure in the Mass Public
M Freeze, JM Montgomery
American Politics Research 44 (3), 415-447, 2016
Calibrating ensemble forecasting models with sparse data in the social sciences
JM Montgomery, FM Hollenbach, MD Ward
International Journal of Forecasting 31 (3), 930-942, 2015
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