Josh Chen
Impact in
- Statistics and Probability top 10%
- Statistical Methods in Clinical Trials
- Advanced Causal Inference Techniques
- Statistical Methods and Inference
Papers in
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- Statistical Methods in Clinical Trials 9
- Advanced Causal Inference Techniques 6
- Statistical Methods and Inference 3
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- Health Systems, Economic Evaluations, Quality of Life 4
- Pharmaceutical Economics and Policy 2
- Co-authors
- Ming Zhu (2 shared papers)Gang Li (5 shared papers)Saranya Sridhar (1 shared paper)Michael Greenberg (1 shared paper)Hui Quan (5 shared papers)Yoko Tanaka (4 shared papers)Ayman Chit (1 shared paper)Sanjay Gurunathan (1 shared paper)
- Journals
- Contemporary Clinical Trials (3 papers)Therapeutic Innovation & Regulatory Science (2 papers)Journal of Biopharmaceutical Statistics (2 papers)Statistics in Biopharmaceutical Research (2 papers)Journal of the Royal Statistical Society Series C (Applied Statistics) (1 paper)
- Partner nations
- United StatesJapanFrance
In The Last Decade
Josh Chen
11 papers receiving 63 citations
Peers
Comparison fields: 5 of 32
- Statistics and Probability 38
- Family Practice 2
- Health 6
- Economics and Econometrics 16
- Statistics, Probability and Uncertainty 4
Countries citing papers authored by Josh Chen
This map shows the geographic impact of Josh Chen'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 Josh Chen with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Josh Chen more than expected).
Fields of papers citing papers by Josh Chen
This network shows the impact of papers produced by Josh Chen. 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 Josh Chen. The network helps show where Josh Chen may publish in the future.
Co-authors
The 25 scholars most cited alongside Josh Chen, 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 | 2019 | 27 | |
| 2 | 2017 | 10 | |
| 3 | 2012 | 7 | |
| 4 | 2013 | 4 | |
| 5 | 2021 | 4 | |
| 6 | 2021 | 4 | |
| 7 | 2023 | 3 | |
| 8 | 2019 | 2 | |
| 9 | 2020 | 1 | |
| 10 | 2008 | 1 | |
| 11 | 2018 | 1 | |
| 12 | 2023 | 0 | |
| 13 | 2025 | 0 |
About Josh Chen
Josh Chen is a scholar working on Statistics and Probability, Economics and Econometrics, Infectious Diseases, Health and Immunology, having authored 13 papers that have together received 64 indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (9 papers), Advanced Causal Inference Techniques (6 papers), Health Systems, Economic Evaluations, Quality of Life (4 papers), Statistical Methods and Inference (3 papers), Vaccine Coverage and Hesitancy (2 papers), Biosimilars and Bioanalytical Methods (2 papers), Pharmaceutical Economics and Policy (2 papers) and SARS-CoV-2 and COVID-19 Research (2 papers). The work is most often cited by research in Statistics and Probability (38 citations), Family Practice (2 citations), Health (6 citations), Economics and Econometrics (16 citations) and Statistics, Probability and Uncertainty (4 citations). Josh Chen has collaborated with scholars based in United States, Japan and France. Frequent co-authors include Ming Zhu, Gang Li, Saranya Sridhar, Michael Greenberg, Hui Quan, Yoko Tanaka, Ayman Chit, Sanjay Gurunathan, Rosalind Hollingsworth and Yining Wang. Their work appears in journals such as Contemporary Clinical Trials, Therapeutic Innovation & Regulatory Science, Journal of Biopharmaceutical Statistics, Statistics in Biopharmaceutical Research and Journal of the Royal Statistical Society Series C (Applied Statistics).
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.