William H. Greene

1.3k citations
9 papers · 959 indexed · 1 hit paper · h-index 7
Topics
Statistical Methods and Bayesian Inference (3 papers)Economic and Environmental Valuation (2 papers)Statistical Methods and Inference (2 papers)

In The Last Decade

William H. Greene

7 papers receiving 919 citations

Hit Papers

Testing hypotheses about interaction terms in nonlinear m...20102026201520202010200400600

Peers

William H. Greene
Comparison fields: 5 of 110
  • Economics and Econometrics 362
  • Accounting 235
  • Sociology and Political Science 181
  • Strategy and Management 180
  • Management Science and Operations Research 136
Replace Marcel Thum with:
Marcel Thum Germany
Jane Leber Herr United States
Joaquim J.S. Ramalho Portugal
Patrice Laroche France
Martı́n A. Rossi Argentina
Salvador Navarro United States
Kevin A. Clarke United States
Vincenzo Verardi Belgium
Isaiah Andrews United States
Thomas S. Ulen United States
William H. Greene relative to Marcel Thum Germany Marcel Thum's profile →
Citations per field
00.5×1.5×
Marcel Thum · 1×
Citations per year

Countries citing papers authored by William H. Greene

Since Specialization
Citations

This map shows the geographic impact of William H. Greene'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 H. Greene with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William H. Greene more than expected).

Fields of papers citing papers by William H. Greene

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by William H. Greene. 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 H. Greene. The network helps show where William H. Greene may publish in the future.

Co-authorship network of co-authors of William H. Greene

This figure shows the co-authorship network connecting the top 25 collaborators of William H. Greene. A scholar is included among the top collaborators of William H. Greene 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 H. Greene. William H. Greene is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

9 of 9 papers shown
#WorkIndexed citations
1 0
2 23
3 0
4 166
5
Testing hypotheses about interaction terms in nonlinear modelsbreakdown →
609
6 46
7 56
8 53
9 6

About William H. Greene

William H. Greene is a scholar working on Statistics and Probability, Critical Care and Intensive Care Medicine and Statistics, Probability and Uncertainty, having authored 9 papers that have together received 959 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (3 papers), Economic and Environmental Valuation (2 papers) and Statistical Methods and Inference (2 papers). The work is most often cited by research in Accounting (235 citations), Economics and Econometrics (362 citations) and Strategy and Management (180 citations). William H. Greene has collaborated with scholars based in United States, Switzerland and Italy. Frequent co-authors include Massimo Filippini, Craig P. Dahlgren, Valeria Pizarro, Krista D. Sherman, Lucy B. Palmer, Girma T. Kassie, Tsedeke Abate, Bekele Shiferaw, Chloe Sutcliffe and Jiwei Li. Their work appears in journals such as American Journal of Respiratory and Critical Care Medicine, Economics Letters and Journal of Visualized Experiments.

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.

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