Tom Leonard

4.2k citations
73 papers · 3.2k · 1 hit paper · h-index 24

Impact in

Papers in

Tom Leonard

68 papers receiving 2.9k citations

Tom Leonard's Hit Papers

Bayes and Empirical Bayes Methods for Data Analysis. 1997 · 688 citations
6880+9+19Years since publication200400600

Peers

Tom Leonard
Comparison fields: 5 of 195
  • Statistics and Probability 1.2k
  • Statistics, Probability and Uncertainty 251
  • Management Science and Operations Research 352
  • Artificial Intelligence 703
  • General Decision Sciences 28
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Tom Leonard relative to Craig Robertson United States Craig Robertson's profile →
Citations per field
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Citations per year

Countries citing papers authored by Tom Leonard

Since Specialization
Citations

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

Fields of papers citing papers by Tom Leonard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tom Leonard. 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 Tom Leonard. The network helps show where Tom Leonard may publish in the future.

Co-authors

The 25 scholars most cited alongside Tom Leonard, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Tom Leonard Line = papers co-authored together Tom Leonard links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 73 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bayes and Empirical Bayes Methods for Data Analysis.
Hit paper breakdown →
1997688
2 1976221
3 1989202
4
A two-item conjoint screen for alcohol and other drug problems.
2001174
5 1998151
6 1978141
7 1996140
8 1992118
9 1992113
10 1998106
11 199794
12 199986
13 197584
14 199778
15
A two-item screening test for alcohol and other drug problems.
199764
16 198946
17 197739
18 200038
19 198234
20 197533

About Tom Leonard

Tom Leonard is a scholar working on Statistics and Probability, Statistics, Probability and Uncertainty, Artificial Intelligence, Atmospheric Science and Management, Monitoring, Policy and Law, having authored 73 papers that have together received 3.2k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (21 papers), Advanced Statistical Methods and Models (13 papers), Statistical Methods and Inference (10 papers), Statistical Distribution Estimation and Applications (7 papers), Bayesian Methods and Mixture Models (6 papers), Cryospheric studies and observations (6 papers), Landslides and related hazards (5 papers) and Advanced Statistical Process Monitoring (5 papers). The work is most often cited by research in Statistics and Probability (1.2k citations), Statistics, Probability and Uncertainty (251 citations), Management Science and Operations Research (352 citations), Artificial Intelligence (703 citations) and General Decision Sciences (28 citations). Tom Leonard has collaborated with scholars based in United Kingdom, United States and Canada. Frequent co-authors include Thomas A. Louis, Orestis Papasouliotis, Anthony O’Hagan, Laura A. Saunders, J.S. Hsu, Kam‐Wah Tsui, Richard L. Brown, Jürgen Pilz, Frank Lad and James O. Berger. Their work appears in journals such as Journal of the American Statistical Association, Biometrika, Biometrics, Psychometrika and Journal of the Royal Statistical Society Series B (Statistical Methodology).

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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