Kosuke Imai
Impact in
- Statistics and Probability top 0.05%
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
- Statistical Methods and Bayesian Inference
-
- Electoral Systems and Political Participation
Papers in
-
- Advanced Causal Inference Techniques 63
- Statistical Methods and Inference 41
- Statistical Methods and Bayesian Inference 35
- Statistical Methods in Clinical Trials 12
- Survey Sampling and Estimation Techniques 10
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- Political Conflict and Governance 10
- Qualitative Comparative Analysis Research 10
- Co-authors
- Dustin Tingley (12 shared papers)Gary King (12 shared papers)Luke Keele (7 shared papers)Daniel E. Ho (10 shared papers)Elizabeth A. Stuart (6 shared papers)Teppei Yamamoto (12 shared papers)Marc Ratkovic (4 shared papers)K. Hirose (3 shared papers)
- Journals
- Political Analysis (16 papers)Journal of the American Statistical Association (12 papers)American Journal of Political Science (9 papers)American Political Science Review (8 papers)Journal of Statistical Software (4 papers)
- Partner nations
- United StatesUnited KingdomJapan
In The Last Decade
Kosuke Imai
137 papers receiving 20.1k citations
Kosuke Imai's Hit Papers
Peers
Comparison fields: 5 of 215
- Statistics and Probability 3.8k
- Political Science and International Relations 2.9k
- Economics and Econometrics 3.2k
- Sociology and Political Science 4.9k
- Safety Research 901
Countries citing papers authored by Kosuke Imai
This map shows the geographic impact of Kosuke Imai's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Kosuke Imai with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Kosuke Imai more than expected).
Fields of papers citing papers by Kosuke Imai
This network shows the impact of papers produced by Kosuke Imai. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Kosuke Imai. The network helps show where Kosuke Imai may publish in the future.
Co-authors
The 25 scholars most cited alongside Kosuke Imai, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
Showing the 20 most-cited of 146 papers — load more, or switch the sort, to bring in the rest.
| # | Work | ||
|---|---|---|---|
| 1 | Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference Hit paper breakdown → | 2007 | 3124 |
| 2 | MatchIt: Nonparametric Preprocessing for Parametric Causal Inference Hit paper breakdown → | 2011 | 3078 |
| 3 | mediation:RPackage for Causal Mediation Analysis Hit paper breakdown → | 2014 | 2701 |
| 4 | A general approach to causal mediation analysis. Hit paper breakdown → | 2010 | 2597 |
| 5 | Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies Hit paper breakdown → | 2011 | 1078 |
| 6 | Covariate Balancing Propensity Score Hit paper breakdown → | 2013 | 805 |
| 7 | Causal Inference With General Treatment Regimes Hit paper breakdown → | 2004 | 589 |
| 8 | Statistical Analysis of List Experiments Hit paper breakdown → | 2012 | 401 |
| 9 | On the Use of Two-Way Fixed Effects Regression Models for Causal Inference with Panel Data Hit paper breakdown → | 2020 | 368 |
| 10 | 2013 | 294 | |
| 11 | Zelig: Everyone's Statistical Software | 2006 | 283 |
| 12 | Identification and Sensitivity Analysis for Multiple Causal Mechanisms: Revisiting Evidence from Framing Experiments Hit paper breakdown → | 2013 | 267 |
| 13 | 2012 | 266 | |
| 14 | 2008 | 265 | |
| 15 | Explaining Support for Combatants during Wartime: A Survey Experiment in Afghanistan Hit paper breakdown → | 2013 | 259 |
| 16 | 2009 | 237 | |
| 17 | When Should We Use Unit Fixed Effects Regression Models for Causal Inference with Longitudinal Data? Hit paper breakdown → | 2019 | 225 |
| 18 | 2011 | 212 | |
| 19 | 2018 | 199 | |
| 20 | 2009 | 191 |
About Kosuke Imai
Kosuke Imai is a scholar working on Statistics and Probability, Sociology and Political Science, Political Science and International Relations, Artificial Intelligence and Economics and Econometrics, having authored 146 papers that have together received 21.0k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (63 papers), Statistical Methods and Inference (41 papers), Statistical Methods and Bayesian Inference (35 papers), Electoral Systems and Political Participation (23 papers), Statistical Methods in Clinical Trials (12 papers), Political Conflict and Governance (10 papers), Qualitative Comparative Analysis Research (10 papers) and Survey Sampling and Estimation Techniques (10 papers). The work is most often cited by research in Statistics and Probability (3.8k citations), Political Science and International Relations (2.9k citations), Economics and Econometrics (3.2k citations), Sociology and Political Science (4.9k citations) and Safety Research (901 citations). Kosuke Imai has collaborated with scholars based in United States, United Kingdom and Japan. Frequent co-authors include Dustin Tingley, Gary King, Luke Keele, Daniel E. Ho, Elizabeth A. Stuart, Teppei Yamamoto, Marc Ratkovic, K. Hirose, David A. van Dyk and Graeme Blair. Their work appears in journals such as Political Analysis, Journal of the American Statistical Association, American Journal of Political Science, American Political Science Review and Journal of Statistical Software.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.