Roy E. Welsch
- Statistics and Probability top 0.1%
- Advanced Statistical Methods and Models 21
- Statistical Methods and Inference 10
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- Advanced Statistical Process Monitoring 12
- Accounting top 0.5%
- Finance top 1%
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- Liver Disease Diagnosis and Treatment 6
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- Artificial Intelligence in Healthcare 5
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- Advanced Text Analysis Techniques 5
- Sentiment Analysis and Opinion Mining 5
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- Cell Image Analysis Techniques 5
- Co-authors
- Edwin KuhDavid A. BelsleyPaul W. HollandDavid C. HoaglinErik CambriaPaul F. VellemanJ. E. DennisWilliam S. Krasker
- Journals
- Journal of the American Statistical Association (9 papers)The American Statistician (8 papers)Computational Statistics & Data Analysis (4 papers)
- Partner nations
- United StatesSingaporeChina
In The Last Decade
Roy E. Welsch
112 papers receiving 11.2k citations
Hit Papers
Peers
Comparison fields: 5 of 233
- Statistics and Probability 2.0k
- Statistics, Probability and Uncertainty 904
- Accounting 1.3k
- Finance 813
- Management Science and Operations Research 895
Countries citing papers authored by Roy E. Welsch
This map shows the geographic impact of Roy E. Welsch'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 Roy E. Welsch with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Roy E. Welsch more than expected).
Fields of papers citing papers by Roy E. Welsch
This network shows the impact of papers produced by Roy E. Welsch. 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 Roy E. Welsch. The network helps show where Roy E. Welsch may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Roy E. Welsch, 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 | 2025 | 1 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 4 | |
| 5 | 2023 | 6 | |
| 6 | 2021 | 10 | |
| 7 | 2019 | 4 | |
| 8 | 2018 | 1 | |
| 9 | 2014 | 51 | |
| 10 | 2014 | 3 | |
| 11 | 2012 | 27 | |
| 12 | 2011 | 3 | |
| 13 | 2011 | 26 | |
| 14 | 2011 | 27 | |
| 15 | 2010 | 12 | |
| 16 | 1996 | 11 | |
| 17 | 1988 | 14 | |
| 18 | 1982 | 211 | |
| 19 | The Hat Matrix in Regression and ANOVAbreakdown → | 1978 | 558 |
| 20 | Linear Regression Diagnostics | 1977 | 25 |
About Roy E. Welsch
Roy E. Welsch is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty and Biophysics, having authored 115 papers that have together received 11.9k indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (21 papers), Advanced Statistical Process Monitoring (12 papers), Statistical Methods and Inference (10 papers), Liver Disease Diagnosis and Treatment (6 papers), Artificial Intelligence in Healthcare (5 papers), Advanced Text Analysis Techniques (5 papers), Sentiment Analysis and Opinion Mining (5 papers) and Cell Image Analysis Techniques (5 papers). The work is most often cited by research in Statistics and Probability (2.0k citations), Statistics, Probability and Uncertainty (904 citations) and Accounting (1.3k citations). Roy E. Welsch has collaborated with scholars based in United States, Singapore and China. Frequent co-authors include Edwin Kuh, David A. Belsley, Paul W. Holland, David C. Hoaglin, Erik Cambria, Paul F. Velleman, J. E. Dennis, William S. Krasker, David M. Gay and Frank Xing. Their work appears in journals such as Journal of the American Statistical Association, The American Statistician, Computational Statistics & Data Analysis, Scientific Reports and PLoS ONE.
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.