Statistical Methods and Bayesian Inference
Statistical Methods and Bayesian Inference is a research topic within Statistics and Probability. Science Explorer counts 29k research works in it since 1950. 20.7% of them reached the world's top 10% most cited for their field and year.
This cluster of papers focuses on various statistical methods and models for handling missing data in research, including multiple imputation, Bayesian modeling, generalized linear models, longitudinal data analysis, and sensitivity analysis. It covers topics such as model complexity, simulation studies, and the application of these methods in different fields. The cluster also discusses the challenges and best practices for analyzing datasets with missing values.
- Multiple Imputation
- Bayesian Modeling
- Generalized Linear Models
- Longitudinal Data Analysis
- Model Complexity
- Statistical Methods
- Mixed-Effects Models
- Simulation Studies
- Structural Equation Modeling
- Sensitivity Analysis
- Research works
- 29k fractional, since 1950
- In the world top 10%
- 5.9k per year above
- Top-10% rate
- 20.7% share of its works in the world top 10%
- Growth, 2013–17 → 2018–22
- +9% the tick is no change
Which countries lead Statistical Methods and Bayesian Inference research?
By volume, the United States and China publish the most (1.3k and 374 works in 2022–2025).
By volume, 2022–2025
- 1 United States 1.3k works
- 2 China 374 works
- 3 India 189 works
- 4 United Kingdom 189 works
- 5 Canada 178 works
- 6 Germany 165 works
- 7 Italy 124 works
- 8 France 108 works
- 9 Saudi Arabia 106 works
- 10 Japan 106 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 and Bayesian Inference research?
By volume in 2022–2025, University of North Carolina at Chapel Hill publishes the most Statistical Methods and Bayesian Inference research, followed by University of Michigan and University of Pennsylvania.
By volume, 2022–2025
- 1 University of North Carolina at Chapel Hill United States 37 works
- 2 University of Michigan United States 27 works
- 3 University of Pennsylvania United States 27 works
- 4 Harvard University United States 24 works
- 5 Stanford University United States 19 works
- 6 Duke University United States 18 works
- 7 University of Washington United States 17 works
- 8 University College London United Kingdom 17 works
- 9 North Carolina State University United States 16 works
- 10 Sapienza University of Rome Italy 16 works
Who are the leading researchers in Statistical Methods and Bayesian Inference?
The most-cited researchers publishing on Statistical Methods and Bayesian Inference include Peter M. Bentler, Robert Tibshirani and Jerome H. Friedman.
- 1 Peter M. Bentler 16k citations
- 2 Robert Tibshirani 13k citations
- 3 Jerome H. Friedman 11k citations
- 4 H. Vincent Poor 9.5k citations
- 5 Kristopher J. Preacher 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 and Bayesian Inference research done?
The largest centres of Statistical Methods and Bayesian Inference research in 2022–2025 are Beijing (China), London (United Kingdom), New York (United States) and Tokyo (Japan).
Largest cities, 2022–2025
- 1 Beijing China 87 works
- 2 London United Kingdom 62 works
- 3 New York United States 52 works
- 4 Tokyo Japan 51 works
- 5 Shanghai China 42 works
- 6 Chapel Hill United States 38 works
- 7 Philadelphia United States 37 works
- 8 Seoul South Korea 37 works
- 9 Paris France 37 works
- 10 Riyadh Saudi Arabia 36 works
Where is the best place to study Statistical Methods and Bayesian Inference?
Among universities, judged by research, Princess Nourah bint Abdulrahman University, Imam Mohammad ibn Saud Islamic University and University of Pennsylvania 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 | Princess Nourah bint Abdulrahman University Saudi Arabia | 65.2 | 31.7% | 10.1× | 10 | — |
| 2 | Imam Mohammad ibn Saud Islamic University Saudi Arabia | 61.1 | 32.6% | 11.4× | 8 | — |
| 3 | University of Pennsylvania United States | 55.5 | 22.4% | 7.6× | 27 | +39.7% |
| 4 | Harvard University United States | 53.4 | 32.1% | 4.9× | 24 | +9.2% |
| 5 | University of Connecticut United States | 49.8 | 14.5% | 10.7× | 15 | +48.2% |
| 6 | University of Missouri United States | 49.6 | 23.4% | 9.3× | 14 | -3.0% |
| 7 | University of Amsterdam Netherlands | 49.2 | 40.0% | 4.3× | 9 | +87.1% |
| 8 | King Abdulaziz University Saudi Arabia | 48.9 | 27.9% | 5.5× | 12 | +83.6% |
| 9 | Duke University United States | 47.9 | 28.8% | 6.5× | 18 | -12.8% |
| 10 | King Mongkut's University of Technology North Bangkok Thailand | 47.7 | 22.2% | 16.3× | 8 | — |
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 and Bayesian Inference research growing?
Output in 2018–2022 was 9% higher than in 2013–2017, peaking in 2022. The fastest-growing topics are Statistical Methods and Bayesian Inference.
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.