Michael R. Chernick
- Internal Medicine top 2%
- Statistics and Probability top 1%
- Advanced Statistical Methods and Models 16
- Statistical Methods and Inference 15
- Statistical Methods in Clinical Trials 6
- Statistical Methods and Bayesian Inference 5
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- Advanced Statistical Process Monitoring 4
- Finance top 5%
- Financial Risk and Volatility Modeling 5
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- Bayesian Methods and Mixture Models 8
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- Stochastic processes and statistical mechanics 4
Michael R. Chernick
64 papers receiving 3.2k citations
Hit Papers
Peers
Comparison fields: 5 of 217
- Internal Medicine 253
- Statistics and Probability 458
- Cardiology and Cardiovascular Medicine 535
- Statistics, Probability and Uncertainty 149
- Finance 207
Countries citing papers authored by Michael R. Chernick
This map shows the geographic impact of Michael R. Chernick'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 Michael R. Chernick with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael R. Chernick more than expected).
Fields of papers citing papers by Michael R. Chernick
This network shows the impact of papers produced by Michael R. Chernick. 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 Michael R. Chernick. The network helps show where Michael R. Chernick may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael R. Chernick, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2013 | 51 | |
| 2 | 2012 | 10 | |
| 3 | 2012 | 14 | |
| 4 | 2011 | 28 | |
| 5 | 2010 | 54 | |
| 6 | 2010 | 45 | |
| 7 | 2009 | 73 | |
| 8 | 2009 | 14 | |
| 9 | 2009 | 73 | |
| 10 | 2007 | 183 | |
| 11 | 2002 | 215 | |
| 12 | 1994 | 15 | |
| 13 | 1991 | 1 | |
| 14 | 1988 | 1 | |
| 15 | 1988 | 11 | |
| 16 | 1985 | 1 | |
| 17 | 1983 | 1 | |
| 18 | 1982 | 2 | |
| 19 | 1982 | 3 | |
| 20 | 1981 | 57 |
About Michael R. Chernick
Michael R. Chernick is a scholar working on Statistics and Probability, Mathematical Physics and Statistics, Probability and Uncertainty, having authored 67 papers that have together received 3.4k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (16 papers), Statistical Methods and Inference (15 papers), Bayesian Methods and Mixture Models (8 papers), Statistical Methods in Clinical Trials (6 papers), Statistical Methods and Bayesian Inference (5 papers), Financial Risk and Volatility Modeling (5 papers), Advanced Statistical Process Monitoring (4 papers) and Stochastic processes and statistical mechanics (4 papers). The work is most often cited by research in Internal Medicine (253 citations), Statistics and Probability (458 citations) and Cardiology and Cardiovascular Medicine (535 citations). Michael R. Chernick has collaborated with scholars based in United States, Australia and United Kingdom. Frequent co-authors include Robert A LaBudde, Stuart J. Connolly, Michael D. Ezekowitz, Amit Parekh, Salim Yusuf, Sean Yang, Paul Reilly, Duke Bahn, Fred Lee and Anil Kumar. Their work appears in journals such as Technometrics, The American Statistician, Journal of Applied Probability, Journal of the American Statistical Association and Computers & Mathematics with Applications.
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.