Adam Glynn
- Sociology and Political Science top 2%
- Political Science and International Relations top 2%
- Statistics and Probability top 1%
- Artificial Intelligence top 5%
- Economics and Econometrics top 5%
- Co-authors
- Kevin M. QuinnMaya SenJacob EisensteinEshwar ChandrasekharanUmashanthi PavalanathanÉric GilbertAnirudh SrinivasanMatthew Blackwell
- Topics
- Advanced Causal Inference Techniques (14 papers)Statistical Methods and Inference (6 papers)Electoral Systems and Political Participation (4 papers)
- Journals
- Journal of the American Statistical AssociationAmerican Political Science ReviewAmerican Journal of Political Science
- Partner nations
- United StatesSwedenDenmark
In The Last Decade
Adam Glynn
30 papers receiving 1.2k citations
Peers
Comparison fields: 5 of 129
- Sociology and Political Science 566
- Political Science and International Relations 309
- Statistics and Probability 276
- Artificial Intelligence 218
- Economics and Econometrics 213
Countries citing papers authored by Adam Glynn
This map shows the geographic impact of Adam Glynn'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 Adam Glynn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Adam Glynn more than expected).
Fields of papers citing papers by Adam Glynn
This network shows the impact of papers produced by Adam Glynn. 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 Adam Glynn. The network helps show where Adam Glynn may publish in the future.
Co-authorship network of co-authors of Adam Glynn
This figure shows the co-authorship network connecting the top 25 collaborators of Adam Glynn. A scholar is included among the top collaborators of Adam Glynn 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 Adam Glynn. Adam Glynn 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 | 0 | |
| 3 | 8 | |
| 4 | 0 | |
| 5 | 6 | |
| 6 | 5 | |
| 7 | 6 | |
| 8 | 16 | |
| 9 | 3 | |
| 10 | 69 | |
| 11 | 2 | |
| 12 | 18 | |
| 13 | 64 | |
| 14 | 5 | |
| 15 | 134 | |
| 16 | 279 | |
| 17 | Strategies of Research Design with Confounding: A Graphical Description ⇤ | 1 |
| 18 | 31 | |
| 19 | 29 | |
| 20 | 229 |
About Adam Glynn
Adam Glynn is a scholar working on Statistics and Probability, Health and Economics and Econometrics, having authored 33 papers that have together received 1.3k indexed citations. Recurring topics across this work include Advanced Causal Inference Techniques (14 papers), Statistical Methods and Inference (6 papers) and Electoral Systems and Political Participation (4 papers). The work is most often cited by research in Statistics and Probability (276 citations), Communication (169 citations) and Gender Studies (142 citations). Adam Glynn has collaborated with scholars based in United States, Sweden and Denmark. Frequent co-authors include Kevin M. Quinn, Maya Sen, Jacob Eisenstein, Eshwar Chandrasekharan, Umashanthi Pavalanathan, Éric Gilbert, Anirudh Srinivasan, Matthew Blackwell, Jon Wakefield and Nahomi Ichino. Their work appears in journals such as Journal of the American Statistical Association, American Political Science Review and American Journal of Political Science.
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.