Simon Day

2.8k total citations
66 papers, 1.7k citations indexed

About

Simon Day is a scholar working on Statistics and Probability, Economics and Econometrics and Statistics, Probability and Uncertainty. According to data from OpenAlex, Simon Day has authored 66 papers receiving a total of 1.7k indexed citations (citations by other indexed papers that have themselves been cited), including 32 papers in Statistics and Probability, 26 papers in Economics and Econometrics and 16 papers in Statistics, Probability and Uncertainty. Recurrent topics in Simon Day's work include Statistical Methods in Clinical Trials (31 papers), Health Systems, Economic Evaluations, Quality of Life (26 papers) and Meta-analysis and systematic reviews (16 papers). Simon Day is often cited by papers focused on Statistical Methods in Clinical Trials (31 papers), Health Systems, Economic Evaluations, Quality of Life (26 papers) and Meta-analysis and systematic reviews (16 papers). Simon Day collaborates with scholars based in United Kingdom, France and United States. Simon Day's co-authors include Gillian Raab, David Graham, Elazar J. Pedhazur, Liora Pedhazur Schmelkin, W R Burnham, Peter Fayers, Nigel Stallard, Martin Posch, Anneliene Hechtelt Jonker and Nelson Kinnersley and has published in prestigious journals such as The Lancet, Nature Reviews Drug Discovery and Biometrics.

In The Last Decade

Simon Day

60 papers receiving 1.6k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Simon Day United Kingdom 19 413 318 239 194 165 66 1.7k
Munyaradzi Dimairo United Kingdom 22 415 1.0× 323 1.0× 218 0.9× 188 1.0× 165 1.0× 49 1.9k
Kit C. B. Roes Netherlands 28 645 1.6× 529 1.7× 377 1.6× 194 1.0× 208 1.3× 143 2.9k
Stéphane Héritier Australia 33 512 1.2× 219 0.7× 187 0.8× 368 1.9× 446 2.7× 133 3.6k
Andrew P. Grieve United Kingdom 25 780 1.9× 376 1.2× 198 0.8× 139 0.7× 198 1.2× 81 2.7k
Gert van Valkenhoef Netherlands 20 319 0.8× 314 1.0× 325 1.4× 118 0.6× 571 3.5× 33 2.6k
Vance W. Berger United States 19 734 1.8× 357 1.1× 328 1.4× 121 0.6× 100 0.6× 76 1.4k
Laura Flight United Kingdom 12 323 0.8× 279 0.9× 205 0.9× 216 1.1× 70 0.4× 28 1.2k
Hubert J. A. Schouten Netherlands 28 269 0.7× 117 0.4× 212 0.9× 161 0.8× 345 2.1× 62 2.9k
Michael L. Cohen United States 11 402 1.0× 199 0.6× 127 0.5× 139 0.7× 149 0.9× 19 1.5k
Deborah R. Zucker United States 16 168 0.4× 196 0.6× 129 0.5× 146 0.8× 85 0.5× 29 1.1k

Countries citing papers authored by Simon Day

Since Specialization
Citations

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

Fields of papers citing papers by Simon Day

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Simon Day

This figure shows the co-authorship network connecting the top 25 collaborators of Simon Day. A scholar is included among the top collaborators of Simon Day 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 Simon Day. Simon Day is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Totton, Nikki, Steven A. Julious, Elizabeth Coates, et al.. (2023). Appropriate design and reporting of superiority, equivalence and non-inferiority clinical trials incorporating a benefit–risk assessment: the BRAINS study including expert workshop. Health Technology Assessment. 27(20). 1–58. 2 indexed citations
2.
Banaschewski, Tobias, Laurent Chouchana, Simon Day, et al.. (2021). c4c: Paediatric pharmacovigilance: Methodological considerations in research and development of medicines for children – A c4c expert group white paper. British Journal of Clinical Pharmacology. 88(12). 4997–5016. 7 indexed citations
3.
Miller, Frank, Sarah Zohar, Nigel Stallard, et al.. (2018). Approaches to sample size calculation for clinical trials in rare diseases. Pharmaceutical Statistics. 17(3). 214–230. 14 indexed citations
4.
Day, Simon, Anneliene Hechtelt Jonker, Lilian Pek Lian Lau, et al.. (2018). Recommendations for the design of small population clinical trials. Orphanet Journal of Rare Diseases. 13(1). 195–195. 73 indexed citations
5.
Pearce, Michael, Siew Wan Hee, Jason Madan, et al.. (2018). Value of information methods to design a clinical trial in a small population to optimise a health economic utility function. BMC Medical Research Methodology. 18(1). 20–20. 10 indexed citations
6.
Hee, Siew Wan, Adrian Willis, Catrin Tudur Smith, et al.. (2017). Does the low prevalence affect the sample size of interventional clinical trials of rare diseases? An analysis of data from the aggregate analysis of clinicaltrials.gov. Orphanet Journal of Rare Diseases. 12(1). 44–44. 38 indexed citations
7.
Day, Simon. (2017). Evidence-Based Medicine and Rare Diseases. Advances in experimental medicine and biology. 207–220. 5 indexed citations
8.
Day, Simon. (2015). Data monitoring committees in clinical trials: best practice, complexities and considerations. Clinical Investigation. 5(7). 615–617. 2 indexed citations
9.
O’Kelly, Michael, Steven A. Julious, Stephen Pyke, et al.. (2010). Making available information from studies sponsored by the pharmaceutical industry: some current practices. Pharmaceutical Statistics. 10(1). 60–69. 6 indexed citations
10.
Pyke, Stephen, Steven A. Julious, Simon Day, et al.. (2010). The potential for bias in reporting of industry‐sponsored clinical trials. Pharmaceutical Statistics. 10(1). 74–79. 13 indexed citations
11.
Day, Simon, et al.. (2008). Assessing the impact of ICH E9. Pharmaceutical Statistics. 7(2). 77–87. 6 indexed citations
12.
Day, Simon, et al.. (2007). Scene segmentation from motion in multispectral imagery to aid automatic human gait recognition. Proceedings of SPIE, the International Society for Optical Engineering/Proceedings of SPIE. 6741. 67410E–67410E.
13.
Day, Simon. (2000). Statistics Notes: Blinding in clinical trials and other studies. BMJ. 321(7259). 504–504. 333 indexed citations
14.
Raab, Gillian, et al.. (2000). How to Select Covariates to Include in the Analysis of a Clinical Trial. Controlled Clinical Trials. 21(4). 330–342. 137 indexed citations
15.
Day, Simon, et al.. (1998). Double Data Entry: What Value, What Price?. Controlled Clinical Trials. 19(1). 15–24. 68 indexed citations
16.
Day, Simon & David Graham. (1991). Sample size estimation for comparing two or more treatment groups in clinical trials. Statistics in Medicine. 10(1). 33–43. 44 indexed citations
17.
Day, Simon & David Graham. (1989). Sample size and power for comparing two or more treatment groups in clinical trials.. BMJ. 299(6700). 663–665. 43 indexed citations
18.
Day, Simon, et al.. (1989). A comparative evaluation of four hearing aid selection procedures. I—Speech discrimination measures of benefit. British Journal of Audiology. 23(3). 185–199. 7 indexed citations
19.
Wong, F.S.L. & Simon Day. (1989). Life‐span of amalgam restorations in primary molars: some results and comments on statistical analyses. Community Dentistry And Oral Epidemiology. 17(5). 248–251. 3 indexed citations
20.
Day, Simon, et al.. (1989). A comparative evaluation of four hearing-aid selection procedures. II—Quality judgements as measures of benefit. British Journal of Audiology. 23(3). 201–206. 14 indexed citations

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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