Jun‐mo Nam

1.5k citations
55 papers · 1.1k · h-index 20

Impact in

Papers in

Jun‐mo Nam

55 papers receiving 1.0k citations

Peers

Jun‐mo Nam
Comparison fields: 5 of 143
  • Statistics and Probability 366
  • Statistics, Probability and Uncertainty 106
  • Otorhinolaryngology 37
  • Management Science and Operations Research 93
  • Cancer Research 101
Replace Donald G. Thomas with:
Donald G. Thomas United States
David Pee United States
Robert P. Gage United States
Catherine Legrand Belgium
Luís Meira‐Machado Portugal
Hongyuan Cao United States
Maurice J. Staquet Belgium
Nikolaus Becker Germany
Ni Zhao United States
Ronald W. Helms United States
Jun‐mo Nam relative to Donald G. Thomas United States Donald G. Thomas's profile →
Citations per field
00.5×8.8×
Donald G. Thomas · 1×
Citations per year

Countries citing papers authored by Jun‐mo Nam

Since Specialization
Citations

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

Fields of papers citing papers by Jun‐mo Nam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jun‐mo Nam. 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 Jun‐mo Nam. The network helps show where Jun‐mo Nam may publish in the future.

Co-authors

The 25 scholars most cited alongside Jun‐mo Nam, 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 Jun‐mo Nam Line = papers co-authored together Jun‐mo Nam links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 1988133
2 198765
3
Carcinogenicity tests of certain environmental and industrial chemicals.
198161
4 199358
5 199057
6 199647
7 196847
8 199944
9 200244
10 199536
11 199835
12 198034
13 199533
14 197632
15 200530
16 199227
17 197027
18 197326
19 201421
20 200520

About Jun‐mo Nam

Jun‐mo Nam is a scholar working on Statistics and Probability, Management Science and Operations Research, Immunology, Statistics, Probability and Uncertainty and Surgery, having authored 55 papers that have together received 1.1k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (21 papers), Statistical Methods and Bayesian Inference (12 papers), Statistical Methods and Inference (11 papers), Advanced Statistical Methods and Models (6 papers), T-cell and B-cell Immunology (5 papers), Reliability and Agreement in Measurement (5 papers), Statistical Methods in Epidemiology (5 papers) and Advanced Causal Inference Techniques (5 papers). The work is most often cited by research in Statistics and Probability (366 citations), Statistics, Probability and Uncertainty (106 citations), Otorhinolaryngology (37 citations), Management Science and Operations Research (93 citations) and Cancer Research (101 citations). Jun‐mo Nam has collaborated with scholars based in United States, Malaysia and Taiwan. Frequent co-authors include John J. Gart, Douglas G. Chapman, William C. Blackwelder, Joseph K. McLaughlin, Joseph Scotto, Deukwoo Kwon, Elizabeth K. Weisburger, John H. Weisburger, Borge M. Ulland and Wong‐Ho Chow. Their work appears in journals such as Biometrics, Statistics in Medicine, Biometrical Journal, American Journal of Epidemiology and JNCI Journal of the National Cancer Institute.

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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