James Wason

9.7k citations
160 papers · 2.8k indexed · 1 hit paper · h-index 27

James Wason

149 papers receiving 2.7k citations

Hit Papers

Adaptive designs in clinical trials: why use them, and ho...4152018202620202023100200300400

Peers

James Wason
Comparison fields: 5 of 157
  • Statistics and Probability 1.0k
  • Management Science and Operations Research 448
  • Statistics, Probability and Uncertainty 254
  • Economics and Econometrics 494
  • Immunology and Allergy 98
Replace Lee‐Jen Wei with:
Lee‐Jen Wei United States
Gernot Wassmer Germany
Margaret Wu United States
Armin Koch Germany
Didier Renard Belgium
Munyaradzi Dimairo United Kingdom
Lisa V. Hampson United Kingdom
Lori McLeod United States
James S. Ware United Kingdom
Hubert J. A. Schouten Netherlands
James Wason relative to Lee‐Jen Wei United States Lee‐Jen Wei's profile →
Citations per field
00.5×11×
Lee‐Jen Wei · 1×
Citations per year

Countries citing papers authored by James Wason

Since Specialization
Citations

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

Fields of papers citing papers by James Wason

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network

The 25 scholars most cited alongside James Wason, 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 James Wason Line = papers co-authored together James Wason links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 20241
2 20240
3 20246
4 20235
5 20231
6 20232
7 20222
8 202212
9 20212
10 202113
11 202116
12 20211
13 202113
14 20203
15 20191
16 20199
17
20182
18 201813
19 201710
20 201581

About James Wason

James Wason is a scholar working on Statistics and Probability, Management Science and Operations Research, Statistics, Probability and Uncertainty, Economics and Econometrics and Applied Psychology, having authored 160 papers that have together received 2.8k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (85 papers), Health Systems, Economic Evaluations, Quality of Life (34 papers), Optimal Experimental Design Methods (29 papers), Advanced Causal Inference Techniques (24 papers), Meta-analysis and systematic reviews (16 papers), Cancer Genomics and Diagnostics (15 papers), Genetic Associations and Epidemiology (11 papers) and Biosimilars and Bioanalytical Methods (9 papers). The work is most often cited by research in Statistics and Probability (1.0k citations), Management Science and Operations Research (448 citations), Statistics, Probability and Uncertainty (254 citations), Economics and Econometrics (494 citations) and Immunology and Allergy (98 citations). James Wason has collaborated with scholars based in United Kingdom, United States and Netherlands. Frequent co-authors include Adrian Mander, Thomas Jaki, Sofía S. Villar, Jack Bowden, Christina Yap, Michael J. Grayling, Lorenzo Trippa, Lynne Stecher, Stephen Sawcer and Munyaradzi Dimairo. Their work appears in journals such as Trials, Statistics in Medicine, Statistical Methods in Medical Research, BMJ Open and Pharmaceutical 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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