Richard M. Royall

9.0k total citations · 3 hit papers
73 papers, 6.2k citations indexed

About

Richard M. Royall is a scholar working on Statistics and Probability, Artificial Intelligence and Surgery. According to data from OpenAlex, Richard M. Royall has authored 73 papers receiving a total of 6.2k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Statistics and Probability, 17 papers in Artificial Intelligence and 6 papers in Surgery. Recurrent topics in Richard M. Royall's work include Statistical Methods and Bayesian Inference (18 papers), Survey Sampling and Estimation Techniques (17 papers) and Bayesian Methods and Mixture Models (13 papers). Richard M. Royall is often cited by papers focused on Statistical Methods and Bayesian Inference (18 papers), Survey Sampling and Estimation Techniques (17 papers) and Bayesian Methods and Mixture Models (13 papers). Richard M. Royall collaborates with scholars based in United States, Taiwan and Canada. Richard M. Royall's co-authors include Jaxk Reeves, William G. Cumberland, Joanne Katz, Jonathan C. Javitt, James M. Tielsch, Harry A. Quigley, Alfred Sommer, Jay Herson, Thomas M. Brushart and William R. Bell and has published in prestigious journals such as New England Journal of Medicine, Journal of Neuroscience and Journal of the American Statistical Association.

In The Last Decade

Richard M. Royall

71 papers receiving 5.7k citations

Hit Papers

Statistical Evidence: A Likelihood Paradigm 1991 2026 2002 2014 1998 1991 1991 200 400 600

Peers

Richard M. Royall
Comparison fields: 5 of 198
  • Statistics and Probability 1.7k
  • Ophthalmology 965
  • Radiology, Nuclear Medicine and Imaging 786
  • Surgery 607
  • Artificial Intelligence 554
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Citations per field, relative to Richard M. Royall
Richard M. Royall · 1×
Citations per year, relative to Richard M. Royall
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Countries citing papers authored by Richard M. Royall

Since Specialization
Citations

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

Fields of papers citing papers by Richard M. Royall

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Richard M. Royall. 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 Richard M. Royall. The network helps show where Richard M. Royall may publish in the future.

Co-authorship network of co-authors of Richard M. Royall

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

All Works

20 of 20 papers shown
# Work Indexed citations
1 11
2 119
3 69
4 101
5 81
6 399
7 3
8 49
9 26
10 129
11
Finite population sampling and inference : a prediction approach
225
12 139
13 25
14 178
15 128
16
Racial Differences in the Cause-Specific Prevalence of Blindness in East Baltimore breakdown →
612
17 150
18 5
19 42
20 5

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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