Michael E. Miller
Impact in
- Statistics and Probability top 2%
- Statistical Methods and Bayesian Inference
- Immunology top 10%
- T-cell and B-cell Immunology
- Immunodeficiency and Autoimmune Disorders
- Immune Response and Inflammation
Papers in
-
- Cell Adhesion Molecules Research 6
-
- Statistical Methods and Bayesian Inference 7
- Statistical Methods in Clinical Trials 5
- Co-authors
- Edward H. IpJanet A. ToozeJaime L. SpeiserJ. Richard LandisLester BakerCh DavisStephen S. RichShree R. Singh
- Journals
- The Journal of Pediatrics (7 papers)Pediatric Research (3 papers)Biometrics (3 papers)Journal of Leukocyte Biology (2 papers)Diabetes (2 papers)
- Partner nations
- United StatesAustraliaNew Zealand
In The Last Decade
Michael E. Miller
61 papers receiving 2.3k citations
Hit Papers
Peers
Comparison fields: 5 of 201
- Statistics and Probability 170
- Immunology 412
- Equine 26
- Nephrology 83
- Rheumatology 163
Countries citing papers authored by Michael E. Miller
This map shows the geographic impact of Michael E. Miller'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 E. Miller with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael E. Miller more than expected).
Fields of papers citing papers by Michael E. Miller
This network shows the impact of papers produced by Michael E. Miller. 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 E. Miller. The network helps show where Michael E. Miller may publish in the future.
Co-authorship network
The 25 scholars most cited alongside Michael E. Miller, 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 | 2024 | 1 | |
| 2 | 2023 | 12 | |
| 3 | A comparison of random forest variable selection methods for classification prediction modeling Hit paper breakdown → | 2019 | 995 |
| 4 | 2016 | 49 | |
| 5 | 2015 | 39 | |
| 6 | 2015 | 67 | |
| 7 | 2014 | 61 | |
| 8 | 2009 | 5 | |
| 9 | 2004 | 9 | |
| 10 | 2002 | 54 | |
| 11 | 2000 | 174 | |
| 12 | 1995 | 9 | |
| 13 | 1988 | 45 | |
| 14 | 1988 | 44 | |
| 15 | 1987 | 6 | |
| 16 | 1985 | 3 | |
| 17 | 1982 | 3 | |
| 18 | 1979 | 1 | |
| 19 | 1972 | 22 | |
| 20 | 1967 | 68 |
About Michael E. Miller
Michael E. Miller is a scholar working on Immunology and Allergy, Statistics and Probability, Nephrology, Immunology and Microbiology, having authored 62 papers that have together received 2.4k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (7 papers), Cell Adhesion Molecules Research (6 papers), Statistical Methods in Clinical Trials (5 papers), Immunodeficiency and Autoimmune Disorders (5 papers), Neonatal Respiratory Health Research (5 papers), Chronic Kidney Disease and Diabetes (4 papers), Neonatal and Maternal Infections (4 papers) and Diabetes Management and Research (3 papers). The work is most often cited by research in Statistics and Probability (170 citations), Immunology (412 citations), Equine (26 citations), Nephrology (83 citations) and Rheumatology (163 citations). Michael E. Miller has collaborated with scholars based in United States, Australia and New Zealand. Frequent co-authors include Edward H. Ip, Janet A. Tooze, Jaime L. Speiser, J. Richard Landis, Lester Baker, Ch Davis, Stephen S. Rich, Shree R. Singh, Anthony Cheung and Shreekumar Pillai. Their work appears in journals such as The Journal of Pediatrics, Pediatric Research, Biometrics, Journal of Leukocyte Biology and Diabetes.
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.