Andrew Gelman
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Cognitive Neuroscience top 5%
- Sociology and Political Science top 10%
- Experimental and Cognitive Psychology top 5%
- Co-authors
- Jennifer HillMasanao YajimaMarcus A. BrubakerPeter LiJiqiang GuoDaniel C. LeeMatthew D. HoffmanMichael Betancourt
- Topics
- Bayesian Methods and Mixture Models (6 papers)Statistical Methods and Bayesian Inference (4 papers)Statistical Methods and Inference (4 papers)
- Journals
- NatureSHILAP Revista de lepidopterologíaJournal of the American Statistical Association
- Partner nations
- United StatesUnited KingdomBelgium
In The Last Decade
Andrew Gelman
28 papers receiving 1.9k citations
Hit Papers
Peers
Comparison fields: 5 of 192
- Statistics and Probability 372
- Artificial Intelligence 266
- Cognitive Neuroscience 256
- Sociology and Political Science 200
- Experimental and Cognitive Psychology 183
Countries citing papers authored by Andrew Gelman
This map shows the geographic impact of Andrew Gelman'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 Andrew Gelman with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Andrew Gelman more than expected).
Fields of papers citing papers by Andrew Gelman
This network shows the impact of papers produced by Andrew Gelman. 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 Andrew Gelman. The network helps show where Andrew Gelman may publish in the future.
Co-authorship network of co-authors of Andrew Gelman
This figure shows the co-authorship network connecting the top 25 collaborators of Andrew Gelman. A scholar is included among the top collaborators of Andrew Gelman based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Andrew Gelman. Andrew Gelman is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 4 | |
| 3 | 1 | |
| 4 | Stan: A Probabilistic Programming Languagebreakdown → | 496 |
| 5 | Why We (Usually) Don't Have to Worry About Multiple Comparisonsbreakdown → | 884 |
| 6 | 144 | |
| 7 | 39 | |
| 8 | 4 | |
| 9 | 34 | |
| 10 | Bayesian Data Analysis Ed. 2 | 13 |
| 11 | 8 | |
| 12 | 4 | |
| 13 | 94 | |
| 14 | 8 | |
| 15 | 28 | |
| 16 | 0 | |
| 17 | 72 | |
| 18 | 3 | |
| 19 | 18 | |
| 20 | 46 |
About Andrew Gelman
Andrew Gelman is a scholar working on Statistics and Probability, General Decision Sciences and History and Philosophy of Science, having authored 29 papers that have together received 2.0k indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (6 papers), Statistical Methods and Bayesian Inference (4 papers) and Statistical Methods and Inference (4 papers). The work is most often cited by research in Statistics and Probability (372 citations), General Decision Sciences (29 citations) and Experimental and Cognitive Psychology (183 citations). Andrew Gelman has collaborated with scholars based in United States, United Kingdom and Belgium. Frequent co-authors include Jennifer Hill, Masanao Yajima, Marcus A. Brubaker, Peter Li, Jiqiang Guo, Daniel C. Lee, Matthew D. Hoffman, Michael Betancourt, Allen Riddell and Ben Goodrich. Their work appears in journals such as Nature, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.
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.