Jonathan Wakefield

2.5k citations
55 papers · 1.7k indexed · h-index 19

Impact in

Papers in

Jonathan Wakefield

51 papers receiving 1.6k citations

Peers

Jonathan Wakefield
Comparison fields: 5 of 166
  • Statistics and Probability 346
  • Health, Toxicology and Mutagenesis 365
  • Health 191
  • Modeling and Simulation 98
  • Economics and Econometrics 368
Replace Ying C. MacNab with:
Ying C. MacNab Canada
Julia E. Kelsall United Kingdom
Maya Petersen United States
Antonio López‐Quílez Spain
Juan J. Abellán Spain
Joshua L. Warren United States
Ikuho Yamada Japan
Laina D. Mercer United States
E. G. Knox United Kingdom
Andrew Thomson United Kingdom
Jonathan Wakefield relative to Ying C. MacNab Canada Ying C. MacNab's profile →
Citations per field
00.5×1.7×
Ying C. MacNab · 1×
Citations per year

Countries citing papers authored by Jonathan Wakefield

Since Specialization
Citations

This map shows the geographic impact of Jonathan Wakefield'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 Jonathan Wakefield with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Jonathan Wakefield more than expected).

Fields of papers citing papers by Jonathan Wakefield

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jonathan Wakefield. 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 Jonathan Wakefield. The network helps show where Jonathan Wakefield may publish in the future.

Co-authors

The 25 scholars most cited alongside Jonathan Wakefield, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Jonathan Wakefield Line = papers co-authored together Jonathan Wakefield links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 55 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2006220
2 2007151
3 2001135
4 2002119
5 200099
6 200498
7 200184
8 200582
9 196182
10 200571
11 199962
12 201558
13 201058
14 201340
15 200438
16 200630
17 199923
18 199821
19 200519
20 200717

About Jonathan Wakefield

Jonathan Wakefield is a scholar working on Statistics and Probability, Economics and Econometrics, Epidemiology, Electrical and Electronic Engineering and Health, Toxicology and Mutagenesis, having authored 55 papers that have together received 1.7k indexed citations. Recurring topics across this work include Statistical Methods and Bayesian Inference (12 papers), Spatial and Panel Data Analysis (10 papers), Air Quality and Health Impacts (9 papers), Silicon and Solar Cell Technologies (7 papers), demographic modeling and climate adaptation (6 papers), Data-Driven Disease Surveillance (6 papers), Statistical Methods and Inference (4 papers) and Economic and Environmental Valuation (4 papers). The work is most often cited by research in Statistics and Probability (346 citations), Health, Toxicology and Mutagenesis (365 citations), Health (191 citations), Modeling and Simulation (98 citations) and Economics and Econometrics (368 citations). Jonathan Wakefield has collaborated with scholars based in United States, United Kingdom and Malawi. Frequent co-authors include Ruth Salway, Julia E. Kelsall, R.C. Newman, Paul Elliott, Sebastien Haneuse, Hil Lyons, Nicky Best, Robert E. Kass, Donna K. Pauler and Sara Morris. Their work appears in journals such as Biostatistics, International Statistical Review, Journal of the American Statistical Association, Electronics Letters and Environmental and Ecological 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.

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