Thomas C. M. Lee

9.1k citations
192 papers · 5.5k indexed · 2 hit papers · h-index 34
Topics
Statistical Methods and Inference (38 papers)Advanced Statistical Methods and Models (30 papers)Image and Signal Denoising Methods (20 papers)

In The Last Decade

Thomas C. M. Lee

176 papers receiving 5.0k citations

Hit Papers

Introduction to the Theory and Practice of Econometrics19892026200120131989201450010001.5k

Peers

Thomas C. M. Lee
Comparison fields: 5 of 210
  • Statistics and Probability 959
  • Economics and Econometrics 912
  • Artificial Intelligence 555
  • Molecular Biology 530
  • Ophthalmology 440
Replace B. M. Brown with:
B. M. Brown United States
Clark Glymour United States
Edna Schechtman Israel
Hannah J. White United Kingdom
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Thomas C. M. Lee relative to B. M. Brown United States B. M. Brown's profile →
Citations per field
00.5×2.8×
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Citations per year

Countries citing papers authored by Thomas C. M. Lee

Since Specialization
Citations

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

Fields of papers citing papers by Thomas C. M. Lee

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Thomas C. M. Lee. 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 Thomas C. M. Lee. The network helps show where Thomas C. M. Lee may publish in the future.

Co-authorship network of co-authors of Thomas C. M. Lee

This figure shows the co-authorship network connecting the top 25 collaborators of Thomas C. M. Lee. A scholar is included among the top collaborators of Thomas C. M. Lee 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 Thomas C. M. Lee. Thomas C. M. Lee 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
#WorkIndexed citations
1 2
2 0
3 0
4 2
5 1
6 1
7 29
8 2
9 0
10 1
11 3
12 0
13 3
14 2
15 0
16 2
17 5
18 2
19 5
20 24

About Thomas C. M. Lee

Thomas C. M. Lee is a scholar working on Statistics and Probability, Ophthalmology and Signal Processing, having authored 192 papers that have together received 5.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (38 papers), Advanced Statistical Methods and Models (30 papers) and Image and Signal Denoising Methods (20 papers). The work is most often cited by research in Statistics and Probability (959 citations), Ophthalmology (440 citations) and Finance (415 citations). Thomas C. M. Lee has collaborated with scholars based in United States, Hong Kong and Canada. Frequent co-authors include Helmut Lütkepohl, William E. Griffiths, Eric R. Ziegel, George G. Judge, Peter Hill, Jeffrey M. Lohr, Craig N. Sawchuk, David F. Tolin, Richard A. Levine and Gabriel A. Rodriguez‐Yam. Their work appears in journals such as Journal of Clinical Investigation, SHILAP Revista de lepidopterología and Journal of the American Statistical Association.

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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