Christopher S. Coffey
- Statistics and Probability top 2%
- Physiology
- Public Health, Environmental and Occupational Health
- Molecular Biology
- Genetics
- Co-authors
- Keith E. MullerDavid B. AllisonGary L. GadburyJohn A. KairallaNianjun LiuNengjun YiRui FengHemant K. Tiwari
- Topics
- Statistical Methods and Bayesian Inference (9 papers)Statistical Methods in Clinical Trials (8 papers)Optimal Experimental Design Methods (4 papers)
- Journals
- The LancetPLoS ONEStroke
- Partner nations
- United StatesUnited KingdomSwitzerland
In The Last Decade
Christopher S. Coffey
25 papers receiving 918 citations
Hit Papers
Peers
Comparison fields: 5 of 145
- Statistics and Probability 170
- Physiology 163
- Public Health, Environmental and Occupational Health 135
- Molecular Biology 123
- Genetics 122
Countries citing papers authored by Christopher S. Coffey
This map shows the geographic impact of Christopher S. Coffey'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 Christopher S. Coffey with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher S. Coffey more than expected).
Fields of papers citing papers by Christopher S. Coffey
This network shows the impact of papers produced by Christopher S. Coffey. 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 Christopher S. Coffey. The network helps show where Christopher S. Coffey may publish in the future.
Co-authorship network of co-authors of Christopher S. Coffey
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher S. Coffey. A scholar is included among the top collaborators of Christopher S. Coffey 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 Christopher S. Coffey. Christopher S. Coffey is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 11 | |
| 2 | National, regional, and global estimates of low birthweight in 2020, with trends from 2000: a systematic analysisbreakdown → | 42 |
| 3 | 51 | |
| 4 | 131 | |
| 5 | 66 | |
| 6 | 6 | |
| 7 | 9 | |
| 8 | 120 | |
| 9 | 22 | |
| 10 | 27 | |
| 11 | 38 | |
| 12 | 151 | |
| 13 | 25 | |
| 14 | 14 | |
| 15 | 30 | |
| 16 | 25 | |
| 17 | 7 | |
| 18 | 13 | |
| 19 | 25 | |
| 20 | 44 |
About Christopher S. Coffey
Christopher S. Coffey is a scholar working on Statistics and Probability, Aging and Statistics, Probability and Uncertainty, having authored 25 papers that have together received 944 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (9 papers), Statistical Methods in Clinical Trials (8 papers) and Optimal Experimental Design Methods (4 papers). The work is most often cited by research in Statistics and Probability (170 citations), Pharmacy (52 citations) and Aging (17 citations). Christopher S. Coffey has collaborated with scholars based in United States, United Kingdom and Switzerland. Frequent co-authors include Keith E. Muller, David B. Allison, Gary L. Gadbury, John A. Kairalla, Nianjun Liu, Nengjun Yi, Rui Feng, Hemant K. Tiwari, Solomon K. Musani and Daniel Shriner. Their work appears in journals such as The Lancet, PLoS ONE and Stroke.
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.