Chris Charlton
- General Health Professions top 10%
- Sociology and Political Science
- Health top 10%
- Pediatrics, Perinatology and Child Health
- Economics and Econometrics
- Co-authors
- George LeckieWilliam J. BrowneJon RasbashFiona SteeleRobert M. FrenchKen M. WallaceKelvyn JonesSusanna K. Elledge
- Topics
- Statistical Methods and Bayesian Inference (1 paper)Manufacturing Process and Optimization (1 paper)Respiratory viral infections research (1 paper)
- Journals
- SHILAP Revista de lepidopterologíaJournal of Statistical SoftwareDesign Studies
- Partner nations
- United KingdomBangladeshUnited States
In The Last Decade
Chris Charlton
7 papers receiving 494 citations
Peers
Comparison fields: 5 of 122
- General Health Professions 99
- Sociology and Political Science 99
- Health 83
- Pediatrics, Perinatology and Child Health 63
- Economics and Econometrics 62
Countries citing papers authored by Chris Charlton
This map shows the geographic impact of Chris Charlton'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 Chris Charlton with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Chris Charlton more than expected).
Fields of papers citing papers by Chris Charlton
This network shows the impact of papers produced by Chris Charlton. 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 Chris Charlton. The network helps show where Chris Charlton may publish in the future.
Co-authorship network of co-authors of Chris Charlton
This figure shows the co-authorship network connecting the top 25 collaborators of Chris Charlton. A scholar is included among the top collaborators of Chris Charlton 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 Chris Charlton. Chris Charlton is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | A User's Guide To Mlwin | 153 |
| 3 | 59 | |
| 4 | Modeling heterogeneous variance-covariance components in two-level multilevel models | 2 |
| 5 | 291 | |
| 6 | Manual supplement for MLwiN Version 2.26 | 4 |
| 7 | 9 |
About Chris Charlton
Chris Charlton is a scholar working on Statistics and Probability, Industrial and Manufacturing Engineering and Infectious Diseases, having authored 7 papers that have together received 519 indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (1 paper), Manufacturing Process and Optimization (1 paper) and Respiratory viral infections research (1 paper). The work is most often cited by research in Health (83 citations), Statistics and Probability (49 citations) and General Health Professions (99 citations). Chris Charlton has collaborated with scholars based in United Kingdom, Bangladesh and United States. Frequent co-authors include George Leckie, William J. Browne, Jon Rasbash, Fiona Steele, Robert M. French, Ken M. Wallace, Kelvyn Jones, Susanna K. Elledge, Rafael Gómez-Sjöberg and Maíra Phelps. Their work appears in journals such as SHILAP Revista de lepidopterología, Journal of Statistical Software and Design Studies.
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.