Imai, Kosuke, Gary King, and Clayton Nall. (2009). ``Rejoinder: Matched Pairs and the Future of Cluster-Randomized Experiments.'' Statistical Science, Vol. 24, No. 1 (February), pp. 65-72.
Sengupta, Souhardya, Kosuke Imai, and Georgia Papadogeorgou
(2025).
``Low-rank Covariate Balancing Estimators under Interference.''
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Mukaigawara, Mitsuru, and Kosuke Imai, Jason Lyall, and Georgia Papadogeorgou
(2025).
``Spatiotemporal causal inference with arbitrary spillover and carryover effects.''
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Zhou, Lingxiao, and Kosuke Imai, Jason Lyall, and Georgia Papadogeorgou
(2025).
``Estimating Heterogeneous Treatment Effects for Spatio-Temporal Causal Inference: How Economic Assistance Moderates the Effects of Airstrikes on Insurgent Violence.''
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Tarr, Alexander and Kosuke Imai
(2025).
``Estimating Average Treatment Effects with Support Vector Machines.''
Statistics in Medicine, Vol. 44, No. 5, e70006.
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Imai, Kosuke, In Song Kim, and Erik Wang
(2023).
``Matching Methods for Causal Inference with Time-Series Cross-Sectional Data.''
American Journal of Political Science, Vol. 67, No. 3 (July), pp. 587-605.
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Fan, Jianqing, Kosuke Imai, Inbeom Lee, Han Liu, Yang Ning, and Xiaolin Yang
(2023).
``Optimal Covariate Balancing Conditions in Propensity Score Estimation.''
Journal of Business & Economic Statistics, Vol. 41, No. 1, pp. 97-110.
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Imai, Kosuke, and Yang Ning
(2023).
``Imai, Kosuke, and Yang Ning. (2023). ``Covariate Balancing Propensity Score.'' Handbook of Matching and Weighting Adjust.''
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Bertsimas, Dimitris, Kosuke Imai, and Michael Lingzhi Li
(2023).
``Distributionally Robust Causal Inference with Observational Data.''
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Papadogeorgou, Georgia, Kosuke Imai, Jason Lyall, and Fan Li
(2022).
``Causal Inference with Spatio-temporal Data: Estimating the Effects of Airstrikes on Insurgent Violence in Iraq.''
Journal of the Royal Statistical Society, Series B (Statistical Methodology), Vol. 84, No. 5 (November), pp. 1969-1999.
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Imai, Kosuke and In Song Kim
(2021).
``On the Use of Two-way Fixed Effects Regression Models for Causal Inference with Panel Data.''
Political Analysis, Vol. 29, No. 3 (July), pp. 405-415.
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Imai, Kosuke and James Lo
(2021).
``Robustness of Empirical Evidence for the Democratic Peace: A Nonparametric Sensitivity Analysis.''
International Organization, Vol. 75, No. 3 (Summer), pp. 901-919.
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Ning, Yang, Sida Peng, and Kosuke Imai
(2020).
``Robust Estimation of Causal Effects via High-Dimensional Covariate Balancing Propensity Score.''
Biometrika, Vol. 107, No. 3 (September), pp. 533-554.
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Zhao, Shandong, David A. van Dyk, and Kosuke Imai
(2020).
``Propensity-Score Based Methods for Causal Inference in Observational Studies with Non-Binary Treatments.''
Statistical Methods in Medical Research, Vol. 29, No. 3 (March), pp. 709-727.
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Imai, Kosuke and In Song Kim
(2019).
``When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data?.''
American Journal of Political Science, Vol. 63, No. 2 (April), pp. 467-490.
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Imai, Kosuke, and Zhichao Jiang
(2018).
``A Sensitivity Analysis for Missing Outcomes Due to Truncation-by-Death under the Matched-Pairs Design.''
Statistics in Medicine, Vol. 37, No. 20 (September), pp. 2907-2922.
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Fong, Christian, Chad Hazlett, and Kosuke Imai
(2018).
``Covariate Balancing Propensity Score for a Continuous Treatment: Application to the Efficacy of Political Advertisements.''
Annals of Applied Statistics, Vol. 12, No. 1, pp. 156-177.
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Imai, Kosuke and Marc Ratkovic
(2015).
``Robust Estimation of Inverse Probability Weights for Marginal Structural Models.''
Journal of the American Statistical Association, Vol. 110, No. 511 (September), pp. 1013-1023.
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Imai, Kosuke and Marc Ratkovic
(2014).
``Covariate Balancing Propensity Score.''
Journal of the Royal Statistical Society, Series B (Statistical Methodology), Vol. 76, No. 1 (January), pp. 243-263.
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Ho, Daniel E., Kosuke Imai, Gary King, and Elizabeth Stuart
(2011).
``MatchIt: Nonparametric Preprocessing for Parametric Causal Inference.''
Journal of Statistical Software, Vol. 42, No. 8 (Special Volume on Political Methodology), pp. 1-28.
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King, Gary, Emmanuela Gakidou, Kosuke Imai, Jason Lakin, Ryan T. Moore, Clayton Nall, Nirmala Ravishankar, Manett Vargas, Martha María Téllez-Rojo, Juan Eugenio Hernández Ávila, Mauricio Hernández Ávila, and Héctor Hernández Llamas
(2009).
``Public Policy for the Poor? A Randomised Assessment of the Mexican Universal Health Insurance Programme.''
(with a comment) The Lancet, Vol. 373, No. 9673 (April), pp. 1447-1454.
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Imai, Kosuke, Gary King, and Clayton Nall
(2009).
``The Essential Role of Pair Matching in Cluster-Randomized Experiments, with Application to the Mexican Universal Health Insurance Evaluation.''
(with discussions and rejoinder) Statistical Science, Vol. 24, No. 1 (February), pp. 29-53.
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Imai, Kosuke
(2008).
``Variance Identification and Efficiency Analysis in Randomized Experiments under the Matched-Pair Design.''
Statistics in Medicine, Vol. 27, No. 24 (October), pp. 4857-4873.
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Imai, Kosuke, Gary King, and Elizabeth A. Stuart
(2008).
``Misunderstandings among Experimentalists and Observationalists about Causal Inference.''
Journal of the Royal Statistical Society, Series A (Statistics in Society), Vol. 171, No. 2 (April), pp. 481-502. Reprinted in Field Experiments and their Critics, D. Teele ed. (2014), New Haven: Yale University Press.
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Ho, Daniel E., Kosuke Imai, Gary King, and Elizabeth A. Stuart
(2007).
``Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference.''
Political Analysis, Vol. 15, No.3 (Summer), pp. 199-236. Winner of Miller Prize.
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Imai, Kosuke
(2005).
``Do Get-Out-The-Vote Calls Reduce Turnout? The Importance of Statistical Methods for Field Experiments.''
American Political Science Review, Vol. 99, No. 2 (May), pp. 283-300.
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Imai, Kosuke, and David A. van Dyk
(2004).
``Causal Inference With General Treatment Regimes: Generalizing the Propensity Score.''
Journal of the American Statistical Association, Vol. 99, No. 467 (September), pp. 854-866.
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