Steve M. Bajgier
- Statistics and Probability top 5%
- Management Science and Operations Research top 10%
- Cardiology and Cardiovascular Medicine
- Pulmonary and Respiratory Medicine
- Control and Systems Engineering
- Co-authors
- Arthur V. HillVictor R. PrybutokRonald P. SavareseMatthew J. DoughertyCarol A. RaviolaDaniel J. AzurinDominic A. DeLaurentisKeith D. Calligaro
- Topics
- Statistics Education and Methodologies (3 papers)Cardiac, Anesthesia and Surgical Outcomes (3 papers)Advanced Statistical Methods and Models (2 papers)
- Cited by
- Statistics and ProbabilityManagement Science and Operations ResearchManagement of Technology and Innovation
- Partner nations
- United States
In The Last Decade
Steve M. Bajgier
12 papers receiving 276 citations
Peers
Comparison fields: 5 of 71
- Statistics and Probability 103
- Management Science and Operations Research 85
- Cardiology and Cardiovascular Medicine 68
- Pulmonary and Respiratory Medicine 61
- Control and Systems Engineering 47
Countries citing papers authored by Steve M. Bajgier
This map shows the geographic impact of Steve M. Bajgier'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 Steve M. Bajgier with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Steve M. Bajgier more than expected).
Fields of papers citing papers by Steve M. Bajgier
This network shows the impact of papers produced by Steve M. Bajgier. 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 Steve M. Bajgier. The network helps show where Steve M. Bajgier may publish in the future.
Co-authorship network of co-authors of Steve M. Bajgier
This figure shows the co-authorship network connecting the top 25 collaborators of Steve M. Bajgier. A scholar is included among the top collaborators of Steve M. Bajgier 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 Steve M. Bajgier. Steve M. Bajgier is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 14 | |
| 3 | 64 | |
| 4 | 11 | |
| 5 | Statistics instruction: the next generation | 8 |
| 6 | 14 | |
| 7 | 33 | |
| 8 | 2 | |
| 9 | 7 | |
| 10 | 2 | |
| 11 | 145 | |
| 12 | A simultaneous equation model of individual attitude and belief formation towards social issues | 1 |
About Steve M. Bajgier
Steve M. Bajgier is a scholar working on Statistics and Probability, Software and Cardiology and Cardiovascular Medicine, having authored 12 papers that have together received 303 indexed citations. Recurring topics across this work include Statistics Education and Methodologies (3 papers), Cardiac, Anesthesia and Surgical Outcomes (3 papers) and Advanced Statistical Methods and Models (2 papers). The work is most often cited by research in Statistics and Probability (103 citations), Management Science and Operations Research (85 citations) and Management of Technology and Innovation (30 citations). Steve M. Bajgier has collaborated with scholars based in United States. Frequent co-authors include Arthur V. Hill, Victor R. Prybutok, Ronald P. Savarese, Matthew J. Dougherty, Carol A. Raviola, Daniel J. Azurin, Dominic A. DeLaurentis, Keith D. Calligaro, Steven C. Simper and Michael S. Saccucci. Their work appears in journals such as Operations Research, Journal of Vascular Surgery and The American Journal of Surgery.
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.