Jun‐mo Nam

1.5k total citations
55 papers, 1.1k citations indexed

About

Jun‐mo Nam is a scholar working on Statistics and Probability, Management Science and Operations Research and Immunology. According to data from OpenAlex, Jun‐mo Nam has authored 55 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 8 papers in Management Science and Operations Research and 6 papers in Immunology. Recurrent topics in Jun‐mo Nam's work include Statistical Methods in Clinical Trials (21 papers), Statistical Methods and Bayesian Inference (12 papers) and Statistical Methods and Inference (11 papers). Jun‐mo Nam is often cited by papers focused on Statistical Methods in Clinical Trials (21 papers), Statistical Methods and Bayesian Inference (12 papers) and Statistical Methods and Inference (11 papers). Jun‐mo Nam collaborates with scholars based in United States, Malaysia and Taiwan. Jun‐mo Nam's co-authors include John J. Gart, Douglas G. Chapman, Joseph K. McLaughlin, William C. Blackwelder, Joseph Scotto, Deukwoo Kwon, Elizabeth K. Weisburger, Zdenek Hrubec, Wong‐Ho Chow and John H. Weisburger and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, American Journal of Epidemiology and Biometrics.

In The Last Decade

Jun‐mo Nam

55 papers receiving 1.0k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Jun‐mo Nam United States 20 366 143 110 106 101 55 1.1k
Donald G. Thomas United States 13 256 0.7× 50 0.3× 68 0.6× 51 0.5× 81 0.8× 25 827
Jason J. Z. Liao United States 11 127 0.3× 66 0.5× 267 2.4× 41 0.4× 23 0.2× 50 915
Robert P. Gage United States 15 443 1.2× 370 2.6× 218 2.0× 30 0.3× 60 0.6× 23 1.5k
Ronald W. Helms United States 20 189 0.5× 54 0.4× 156 1.4× 24 0.2× 18 0.2× 59 2.2k
Edward L. Frome United States 13 135 0.4× 38 0.3× 73 0.7× 23 0.2× 73 0.7× 24 797
Maurice J. Staquet Belgium 15 99 0.3× 79 0.6× 129 1.2× 55 0.5× 30 0.3× 23 822
Gregory C. Critchfield United States 13 61 0.2× 131 0.9× 54 0.5× 56 0.5× 139 1.4× 32 1.1k
Luís Meira‐Machado Portugal 13 331 0.9× 95 0.7× 88 0.8× 17 0.2× 38 0.4× 53 904
Laura Thompson United States 11 375 1.0× 48 0.3× 27 0.2× 71 0.7× 16 0.2× 34 706
Hongyuan Cao United States 16 101 0.3× 209 1.5× 53 0.5× 15 0.1× 63 0.6× 63 908

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-authorship network of co-authors of Jun‐mo Nam

This figure shows the co-authorship network connecting the top 25 collaborators of Jun‐mo Nam. A scholar is included among the top collaborators of Jun‐mo Nam 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 Jun‐mo Nam. Jun‐mo Nam 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
1.
Nam, Jun‐mo. (2011). Power and sample size requirements for non-inferiority in studies comparing two matched proportions where the events are correlated. Computational Statistics & Data Analysis. 55(10). 2880–2887. 5 indexed citations
2.
Nam, Jun‐mo. (2009). Efficient interval estimation of a ratio of marginal probabilities in matched‐pair data: Non‐iterative method. Statistics in Medicine. 28(23). 2929–2935. 10 indexed citations
3.
Nam, Jun‐mo. (2006). Non‐inferiority of New Procedure to Standard Procedure in Stratified Matched‐Pair Design. Biometrical Journal. 48(6). 966–977. 10 indexed citations
4.
Nam, Jun‐mo. (2006). Comparison of validity of assessment methods using indices of adjusted agreement. Statistics in Medicine. 26(3). 620–632. 9 indexed citations
5.
Nam, Jun‐mo. (2005). Assessment on homogeneity tests for kappa statistics under equal prevalence across studies in reliability. Statistics in Medicine. 25(9). 1521–1531. 6 indexed citations
6.
7.
Nam, Jun‐mo & William C. Blackwelder. (2002). Analysis of the ratio of marginal probabilities in a matched‐pair setting. Statistics in Medicine. 21(5). 689–699. 44 indexed citations
8.
Nam, Jun‐mo. (2000). Interval Estimation of the Kappa Coefficient with Binary Classification and an Equal Marginal Probability Model. Biometrics. 56(2). 583–585. 16 indexed citations
9.
Hohman, Patricia, Terri Warren, Anna Wald, et al.. (1999). Association of Major Histocompatibility Complex Determinants with the Development of Symptomatic and Asymptomatic Genital Herpes Simplex Virus Type 2 Infections. The Journal of Infectious Diseases. 179(5). 1077–1085. 44 indexed citations
10.
Manns, Angela, Jun‐mo Nam, William Blattner, et al.. (1998). Human Leukocyte Antigen Class II Alleles Associated With Human T-Cell Lymphotropic Virus Type I Infection and Adult T-Cell Leukemia/Lymphoma in a Black Population. JNCI Journal of the National Cancer Institute. 90(8). 617–622. 35 indexed citations
11.
Hsing, Ann W., Jun‐mo Nam, Harvey T. Co Chien, Joseph K. McLaughlin, & Joseph F. Fraumeni. (1996). Risk factors for adrenal cancer: An exploratory study. International Journal of Cancer. 65(4). 432–436. 47 indexed citations
12.
13.
Chow, Wong‐Ho, Joseph K. McLaughlin, Zdenek Hrubec, Jun‐mo Nam, & William J. Blot. (1993). Tobacco use and nasopharyngeal carcinoma in a cohort of us veterans. International Journal of Cancer. 55(4). 538–540. 58 indexed citations
14.
Nam, Jun‐mo & Thomas R. Fears. (1992). Control sample size when cases are given in constant ratio stratum‐matched case‐control studies. Statistics in Medicine. 11(13). 1759–1766. 2 indexed citations
15.
Nam, Jun‐mo & Thomas R. Fears. (1992). Optimum sample size determination in stratified case‐control studies with cost considerations. Statistics in Medicine. 11(4). 547–556. 5 indexed citations
16.
Nam, Jun‐mo & Thomas R. Fears. (1990). Optimum allocation of samples in strata‐matching case‐control studies when cost per sample differs from stratum to stratum. Statistics in Medicine. 9(12). 1475–1483. 8 indexed citations
17.
Fabsitz, Richard R., et al.. (1989). HLA Associations with Obesity. Human Heredity. 39(3). 156–164. 7 indexed citations
18.
Gart, John J. & Jun‐mo Nam. (1988). Approximate Interval Estimation of the Ratio of Binomial Parameters: A Review and Corrections for Skewness. Biometrics. 44(2). 323–323. 133 indexed citations
19.
Nam, Jun‐mo. (1987). A Simple Approximation for Calculating Sample Sizes for Detecting Linear Trend in Proportions. Biometrics. 43(3). 701–701. 65 indexed citations
20.
Nam, Jun‐mo. (1983). Efficient method for identification of cyclic trends in incidence. Communication in Statistics- Theory and Methods. 12(9). 1053–1068. 10 indexed citations

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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