Statistical Methods in Clinical Trials
Statistical Methods in Clinical Trials is a research topic within Statistics and Probability. Science Explorer counts 27k research works in it since 1950. 21.2% of them reached the world's top 10% most cited for their field and year.
This cluster of papers covers a wide range of statistical methods and design considerations in the context of clinical trials and drug development. It includes topics such as controlling the false discovery rate, adaptive trial designs, noninferiority trials, biomarkers, phase I trials, multiple testing, Bayesian methods, sample size determination, composite endpoints, and pharmacokinetic/pharmacodynamic modeling.
- False Discovery Rate
- Adaptive Designs
- Noninferiority Trials
- Biomarkers
- Phase I Trials
- Multiple Testing
- Bayesian Methods
- Sample Size
- Composite Endpoints
- Pharmacokinetic/Pharmacodynamic Modeling
- Research works
- 27k fractional, since 1950
- In the world top 10%
- 5.8k per year above
- Top-10% rate
- 21.2% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +10% the tick is no change
Which countries lead Statistical Methods in Clinical Trials research?
By volume, the United States and the United Kingdom publish the most (1.8k and 337 works in 2022–2025).
By volume, 2022–2025
- 1 United States 1.8k works
- 2 United Kingdom 337 works
- 3 China 279 works
- 4 Germany 221 works
- 5 Canada 176 works
- 6 India 161 works
- 7 France 140 works
- 8 Japan 124 works
- 9 Netherlands 123 works
- 10 Italy 117 works
How concentrated that is
The same countries as shares of everything the list above accounts for. A node where two countries do two thirds of the work and one spread evenly across twelve read alike as a ranking and not at all alike here.
Shares of the rows listed above, not of the whole node.
Which institutions lead Statistical Methods in Clinical Trials research?
By volume in 2022–2025, University of North Carolina at Chapel Hill publishes the most Statistical Methods in Clinical Trials research, followed by Harvard University and The University of Texas MD Anderson Cancer Center.
By volume, 2022–2025
- 1 University of North Carolina at Chapel Hill United States 45 works
- 2 Harvard University United States 33 works
- 3 The University of Texas MD Anderson Cancer Center United States 33 works
- 4 United States Food and Drug Administration United States 28 works
- 5 Duke University United States 28 works
- 6 Pfizer (United States) United States 26 works
- 7 Center for Drug Evaluation and Research United States 26 works
- 8 University of Pennsylvania United States 26 works
- 9 University of Michigan United States 24 works
- 10 Stanford University United States 23 works
Who are the leading researchers in Statistical Methods in Clinical Trials?
The most-cited researchers publishing on Statistical Methods in Clinical Trials include David Moher, Douglas G. Altman and Robert Tibshirani.
- 1 David Moher 38k citations
- 2 Douglas G. Altman 23k citations
- 3 Robert Tibshirani 13k citations
- 4 John P. A. Ioannidis 8k citations
- 5 Gordon Guyatt 6.8k citations
Ranked by citations received across their whole record, among researchers with at least three works on this topic.
Where is Statistical Methods in Clinical Trials research done?
The largest centres of Statistical Methods in Clinical Trials research in 2022–2025 are London (United Kingdom), New York (United States), Beijing (China) and Cambridge (United States). Among places with at least 20 works in it, it is an unusually large share of all research in Silver Spring.
Largest cities, 2022–2025
- 1 London United Kingdom 119 works
- 2 New York United States 106 works
- 3 Beijing China 70 works
- 4 Cambridge United States 61 works
- 5 Boston United States 58 works
- 6 Silver Spring United States 57 works
- 7 Paris France 57 works
- 8 Tokyo Japan 55 works
- 9 Houston United States 48 works
- 10 Chapel Hill United States 47 works
Where it is the local speciality
- Silver SpringUS · 57.2 works66×
Location quotient: how much more of its research is in Statistical Methods in Clinical Trials than the world average.
Where is the best place to study Statistical Methods in Clinical Trials?
Among universities, judged by research, Harvard University, Duke University and Medical University of Vienna score highest, combining excellence, specialisation, size, growth and international reach. Research strength is one signal when choosing where to study; it does not measure teaching.
One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.
| # | University | Score | Top 10% | Specialisation | Works | Growth |
|---|---|---|---|---|---|---|
| 1 | Harvard University United States | 58.8 | 32.4% | 6.4× | 33 | +21.4% |
| 2 | Duke University United States | 56.2 | 20.4% | 9.7× | 28 | +40.4% |
| 3 | Medical University of Vienna Austria | 51.4 | 40.7% | 6.5× | 8 | +58.8% |
| 4 | University College London United Kingdom | 50.7 | 33.3% | 4.0× | 22 | +54.7% |
| 5 | Stanford University United States | 49.5 | 32.8% | 4.6× | 23 | +45.0% |
| 6 | University of North Carolina at Chapel Hill United States | 45.9 | 8.9% | 6.5× | 45 | +92.6% |
| 7 | University of Pennsylvania United States | 45.1 | 20.0% | 6.8× | 26 | +12.7% |
| 8 | Yale University United States | 43.6 | 28.9% | 5.1× | 21 | +1.3% |
| 9 | University of California, San Francisco United States | 43.4 | 34.8% | 5.4× | 14 | -14.0% |
| 10 | University of Sheffield United Kingdom | 42.5 | 31.4% | 5.5× | 12 | +16.9% |
Universities only. Score blends excellence (30%), specialisation (25%), size (20%), growth (15%) and international reach (10%), 2015–2022; growth compares 2010–14 with 2015–19.
Is Statistical Methods in Clinical Trials research growing?
Output in 2018–2022 was 10% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Statistical Methods in Clinical Trials.
The same series as a ribbon — one cell per year, darker for more. The line above answers how much; this answers when.
Which topics inside it are moving
Growth and decline on one axis around a shared zero. Two lists side by side hide the thing that matters: whether the growth dwarfs the decline, or the other way round.