Lawrence J. Brunner
- Statistics and Probability top 5%
- Plant Science
- Cardiology and Cardiovascular Medicine
- Artificial Intelligence top 10%
- Experimental and Cognitive Psychology top 10%
- Co-authors
- Peter C. AustinAlbert Y. LoMark S. RidgwayBrian J. ShuterNicholas C. CollinsJames B. AndersonLinda M. KohnYatika Kohli
- Topics
- Bayesian Methods and Mixture Models (4 papers)Statistical Methods and Bayesian Inference (3 papers)Health Systems, Economic Evaluations, Quality of Life (3 papers)
- Partner nations
- CanadaUnited StatesHong Kong
In The Last Decade
Lawrence J. Brunner
16 papers receiving 777 citations
Peers
Comparison fields: 5 of 152
- Statistics and Probability 134
- Plant Science 121
- Cardiology and Cardiovascular Medicine 120
- Artificial Intelligence 113
- Experimental and Cognitive Psychology 78
Countries citing papers authored by Lawrence J. Brunner
This map shows the geographic impact of Lawrence J. Brunner'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 Lawrence J. Brunner with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Lawrence J. Brunner more than expected).
Fields of papers citing papers by Lawrence J. Brunner
This network shows the impact of papers produced by Lawrence J. Brunner. 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 Lawrence J. Brunner. The network helps show where Lawrence J. Brunner may publish in the future.
Co-authorship network of co-authors of Lawrence J. Brunner
This figure shows the co-authorship network connecting the top 25 collaborators of Lawrence J. Brunner. A scholar is included among the top collaborators of Lawrence J. Brunner 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 Lawrence J. Brunner. Lawrence J. Brunner is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 126 | |
| 2 | 13 | |
| 3 | 167 | |
| 4 | 95 | |
| 5 | 22 | |
| 6 | 10 | |
| 7 | 87 | |
| 8 | 14 | |
| 9 | 122 | |
| 10 | 4 | |
| 11 | 5 | |
| 12 | 13 | |
| 13 | 43 | |
| 14 | 5 | |
| 15 | 34 | |
| 16 | 80 |
About Lawrence J. Brunner
Lawrence J. Brunner is a scholar working on Statistics and Probability, Oral Surgery and Health Information Management, having authored 16 papers that have together received 840 indexed citations. Recurring topics across this work include Bayesian Methods and Mixture Models (4 papers), Statistical Methods and Bayesian Inference (3 papers) and Health Systems, Economic Evaluations, Quality of Life (3 papers). The work is most often cited by research in Statistics and Probability (134 citations), Family Practice (22 citations) and Geriatrics and Gerontology (30 citations). Lawrence J. Brunner has collaborated with scholars based in Canada, United States and Hong Kong. Frequent co-authors include Peter C. Austin, Albert Y. Lo, Mark S. Ridgway, Brian J. Shuter, Nicholas C. Collins, James B. Anderson, Linda M. Kohn, Yatika Kohli, Michael G. Milgroom and R. A. A. Morrall. Their work appears in journals such as Journal of Personality and Social Psychology, Ecology and Molecular Ecology.
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.