Chin‐Shang Li
Impact in
- Genetics top 1%
- Hemoglobinopathies and Related Disorders
- Statistics and Probability top 1%
- Statistical Methods and Bayesian Inference
- Statistical Methods and Inference
Papers in
-
- Statistical Methods and Inference 28
- Statistical Methods and Bayesian Inference 25
- Advanced Statistical Methods and Models 15
- Statistical Distribution Estimation and Applications 10
- Genetics 21
- Hemoglobinopathies and Related Disorders 14
- Co-authors
- Masud SeyalLisa M. BatemanWinfred C. WangTzu‐Chun LinM. Beth McCarvilleJane S. HankinsSanford AuerbachSteven D. Brass
- Journals
- Pediatric Blood & Cancer (7 papers)Epilepsia (5 papers)Journal of Surgical Research (5 papers)PLoS ONE (4 papers)Annals of Plastic Surgery (3 papers)
- Partner nations
- United StatesTaiwanVietnam
In The Last Decade
Chin‐Shang Li
187 papers receiving 4.4k citations
Peers
Comparison fields: 5 of 178
- Genetics 623
- Statistics and Probability 338
- Hematology 454
- Psychiatry and Mental health 501
- Endocrine and Autonomic Systems 157
Countries citing papers authored by Chin‐Shang Li
This map shows the geographic impact of Chin‐Shang Li'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 Chin‐Shang Li with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chin‐Shang Li more than expected).
Fields of papers citing papers by Chin‐Shang Li
This network shows the impact of papers produced by Chin‐Shang Li. 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 Chin‐Shang Li. The network helps show where Chin‐Shang Li may publish in the future.
Co-authors
The 25 scholars most cited alongside Chin‐Shang Li, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2025 | 1 | |
| 2 | 2025 | 0 | |
| 3 | 2022 | 6 | |
| 4 | 2022 | 3 | |
| 5 | 2017 | 39 | |
| 6 | 2016 | 60 | |
| 7 | 2016 | 21 | |
| 8 | 2016 | 20 | |
| 9 | 2015 | 2 | |
| 10 | 2015 | 7 | |
| 11 | Depression, perceived stress and nervios associated with injury in the MICASA Study, a California farm worker population | 2014 | 3 |
| 12 | 2014 | 6 | |
| 13 | 2013 | 36 | |
| 14 | 2011 | 1 | |
| 15 | 2010 | 11 | |
| 16 | 2010 | 5 | |
| 17 | 2010 | 29 | |
| 18 | 2007 | 0 | |
| 19 | 2007 | 31 | |
| 20 | TESTING LACK-OF-FIT OF PARAMETRIC REGRESSION MODELS USING NONPARAMETRIC REGRESSION TECHNIQUES | 2005 | 10 |
About Chin‐Shang Li
Chin‐Shang Li is a scholar working on Statistics and Probability, Genetics, Geriatrics and Gerontology, Dermatology and Hematology, having authored 202 papers that have together received 4.5k indexed citations. Recurring topics across this work include Statistical Methods and Inference (28 papers), Statistical Methods and Bayesian Inference (25 papers), Advanced Statistical Methods and Models (15 papers), Hemoglobinopathies and Related Disorders (14 papers), Bayesian Methods and Mixture Models (12 papers), Sarcoma Diagnosis and Treatment (10 papers), Statistical Distribution Estimation and Applications (10 papers) and Iron Metabolism and Disorders (9 papers). The work is most often cited by research in Genetics (623 citations), Statistics and Probability (338 citations), Hematology (454 citations), Psychiatry and Mental health (501 citations) and Endocrine and Autonomic Systems (157 citations). Chin‐Shang Li has collaborated with scholars based in United States, Taiwan and Vietnam. Frequent co-authors include Masud Seyal, Lisa M. Bateman, Winfred C. Wang, Tzu‐Chun Lin, M. Beth McCarville, Jane S. Hankins, Sanford Auerbach, Steven D. Brass, Robert J. Canter and Jye‐Chyi Lu. Their work appears in journals such as Pediatric Blood & Cancer, Epilepsia, Journal of Surgical Research, PLoS ONE and Annals of Plastic Surgery.
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.