William M. Stanish
- Pulmonary and Respiratory Medicine
- Public Health, Environmental and Occupational Health
- Endocrinology, Diabetes and Metabolism
- Statistics and Probability top 5%
- Physiology
- Co-authors
- A.W. MeikleGary G. KochNoël TaylorJ. Richard LandisJean L. FreemanDee W. WestH. William BarkmanAttilio D. Renzetti
- Topics
- Advanced Statistical Methods and Models (3 papers)Statistical Methods and Bayesian Inference (2 papers)Hormonal and reproductive studies (2 papers)
- Cited by
- Statistics and ProbabilityEndocrinology, Diabetes and MetabolismPulmonary and Respiratory Medicine
- Journals
- The Journal of Clinical Endocrinology & MetabolismAmerican Journal of Public HealthBiometrics
- Partner nations
- United States
In The Last Decade
William M. Stanish
14 papers receiving 519 citations
Peers
Comparison fields: 5 of 119
- Pulmonary and Respiratory Medicine 152
- Public Health, Environmental and Occupational Health 95
- Endocrinology, Diabetes and Metabolism 82
- Statistics and Probability 77
- Physiology 73
Countries citing papers authored by William M. Stanish
This map shows the geographic impact of William M. Stanish'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 William M. Stanish with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William M. Stanish more than expected).
Fields of papers citing papers by William M. Stanish
This network shows the impact of papers produced by William M. Stanish. 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 William M. Stanish. The network helps show where William M. Stanish may publish in the future.
Co-authorship network of co-authors of William M. Stanish
This figure shows the co-authorship network connecting the top 25 collaborators of William M. Stanish. A scholar is included among the top collaborators of William M. Stanish 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 William M. Stanish. William M. Stanish is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Energy intake: its relationship to colon cancer risk. | 92 |
| 2 | Categorical data analysis strategies using SAS software | 2 |
| 3 | 26 | |
| 4 | 8 | |
| 5 | 51 | |
| 6 | 58 | |
| 7 | 1 | |
| 8 | 82 | |
| 9 | 56 | |
| 10 | 85 | |
| 11 | 1 | |
| 12 | 6 | |
| 13 | 3 | |
| 14 | 28 | |
| 15 | 101 |
About William M. Stanish
William M. Stanish is a scholar working on Statistics and Probability, Obstetrics and Gynecology and Endocrinology, Diabetes and Metabolism, having authored 15 papers that have together received 600 indexed citations. Recurring topics across this work include Advanced Statistical Methods and Models (3 papers), Statistical Methods and Bayesian Inference (2 papers) and Hormonal and reproductive studies (2 papers). The work is most often cited by research in Statistics and Probability (77 citations), Endocrinology, Diabetes and Metabolism (82 citations) and Pulmonary and Respiratory Medicine (152 citations). William M. Stanish has collaborated with scholars based in United States. Frequent co-authors include A.W. Meikle, Gary G. Koch, Noël Taylor, J. Richard Landis, Jean L. Freeman, Dee W. West, H. William Barkman, Attilio D. Renzetti, Melville R. Klauber and Richard E. Kanner. Their work appears in journals such as The Journal of Clinical Endocrinology & Metabolism, American Journal of Public Health and Biometrics.
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.