RJ Glynn
- Pharmacology top 0.5%
- Cardiology and Cardiovascular Medicine top 5%
- Endocrinology, Diabetes and Metabolism top 5%
- Economics and Econometrics top 5%
- Statistics and Probability top 2%
- Co-authors
- Jerry AvornMark MonaneJerry H. GurwitzR LevinRhonda L. BohnSteven G. E. MarshDeepak VooraP. M. Ridker
- Topics
- Pharmacogenetics and Drug Metabolism (2 papers)Alcohol Consumption and Health Effects (2 papers)Blood Pressure and Hypertension Studies (2 papers)
- Partner nations
- United StatesUnited Kingdom
In The Last Decade
RJ Glynn
19 papers receiving 1.4k citations
Hit Papers
Peers
Comparison fields: 5 of 124
- Pharmacology 527
- Cardiology and Cardiovascular Medicine 355
- Endocrinology, Diabetes and Metabolism 240
- Economics and Econometrics 228
- Statistics and Probability 184
Countries citing papers authored by RJ Glynn
This map shows the geographic impact of RJ 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 RJ Glynn with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites RJ Glynn more than expected).
Fields of papers citing papers by RJ Glynn
This network shows the impact of papers produced by RJ 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 RJ Glynn. The network helps show where RJ Glynn may publish in the future.
Co-authorship network of co-authors of RJ Glynn
This figure shows the co-authorship network connecting the top 25 collaborators of RJ Glynn. A scholar is included among the top collaborators of RJ 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 RJ Glynn. RJ 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 | Understanding Bias Amplification | 4 |
| 2 | 95 | |
| 3 | 70 | |
| 4 | Use of Pharmacogenetic and Clinical Factors to Predict the Therapeutic Dose of Warfarinbreakdown → | 595 |
| 5 | 114 | |
| 6 | 1 | |
| 7 | Alcohol consumption and the risk of renal dysfunction in apparently healthy men | 2 |
| 8 | 17 | |
| 9 | Alcohol and the risk of renal dysfunction in apparently healthy men. | 1 |
| 10 | 1 | |
| 11 | 0 | |
| 12 | 37 | |
| 13 | 50 | |
| 14 | 49 | |
| 15 | 30 | |
| 16 | 206 | |
| 17 | 14 | |
| 18 | 115 | |
| 19 | 13 | |
| 20 | Selection modelling versus mixture modelling with nonignorable nonresponse | 26 |
About RJ Glynn
RJ Glynn is a scholar working on Family Practice, Statistics, Probability and Uncertainty and Statistics and Probability, having authored 20 papers that have together received 1.4k indexed citations. Recurring topics across this work include Pharmacogenetics and Drug Metabolism (2 papers), Alcohol Consumption and Health Effects (2 papers) and Blood Pressure and Hypertension Studies (2 papers). The work is most often cited by research in Family Practice (139 citations), Pharmacology (527 citations) and Geriatrics and Gerontology (106 citations). RJ Glynn has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Jerry Avorn, Mark Monane, Jerry H. Gurwitz, R Levin, Rhonda L. Bohn, Steven G. E. Marsh, Deepak Voora, P. M. Ridker, DL Veenstra and Brian F. Gage. Their work appears in journals such as Blood, American Journal of Epidemiology and American Journal of Public Health.
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.