Nigel Stallard

9.4k citations
193 papers · 4.4k · h-index 36

Impact in

Papers in

Nigel Stallard

188 papers receiving 4.3k citations

Peers

Nigel Stallard
Comparison fields: 5 of 171
  • Statistics and Probability 2.0k
  • Management Science and Operations Research 1.2k
  • Statistics, Probability and Uncertainty 273
  • Economics and Econometrics 789
  • Applied Psychology 115
Replace Adrian Mander with:
Adrian Mander United Kingdom
Thomas Jaki United Kingdom
Dean Follmann United States
David M. Zucker Israel
Margaret Wu United States
Susan S. Ellenberg United States
Steven Teerenstra Netherlands
Anne Whitehead United Kingdom
Elizabeth L. Turner United States
Walter Lehmacher Germany
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Citations per field
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Citations per year

Countries citing papers authored by Nigel Stallard

Since Specialization
Citations

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

Fields of papers citing papers by Nigel Stallard

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

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

All Works

20 of 20 papers shown

Showing the 20 most-cited of 193 papers — load more, or switch the sort, to bring in the rest.

#Work
1 2016200
2 2001167
3 2010164
4 2003134
5 2019124
6 2012121
7 2006119
8 200881
9 201580
10 201179
11 201873
12 201071
13 201268
14 200763
15 200963
16 200860
17 200759
18 199858
19 202156
20 201256

About Nigel Stallard

Nigel Stallard is a scholar working on Statistics and Probability, Management Science and Operations Research, Economics and Econometrics, Pathology and Forensic Medicine and General Health Professions, having authored 193 papers that have together received 4.4k indexed citations. Recurring topics across this work include Statistical Methods in Clinical Trials (105 papers), Optimal Experimental Design Methods (60 papers), Health Systems, Economic Evaluations, Quality of Life (49 papers), Advanced Causal Inference Techniques (21 papers), Statistical Methods and Bayesian Inference (12 papers), Statistical Methods and Inference (11 papers), Musculoskeletal pain and rehabilitation (9 papers) and Biosimilars and Bioanalytical Methods (8 papers). The work is most often cited by research in Statistics and Probability (2.0k citations), Management Science and Operations Research (1.2k citations), Statistics, Probability and Uncertainty (273 citations), Economics and Econometrics (789 citations) and Applied Psychology (115 citations). Nigel Stallard has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Susan Todd, Tim Friede, Nick Parsons, John Whitehead, Thomas Hamborg, Sarah Stewart‐Brown, Peter Kimani, Anne Whitehead, William F. Rosenberger and D. Simkiss. Their work appears in journals such as Statistics in Medicine, Trials, Journal of Biopharmaceutical Statistics, Human & Experimental Toxicology and Biometrical Journal.

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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