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Advanced Statistical Modeling Techniques

Advanced Statistical Modeling Techniques is a research topic within Computer Networks and Communications. Science Explorer counts 5.5k research works in it since 1950. 10.1% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on the development and application of secure classical communication systems using Johnson noise and Kirchhoff's law. It also explores person-oriented research, machine learning algorithms, directional dependence analysis, and statistical packages like ROPstat for data analysis.

  • Secure Communication
  • Johnson Noise
  • Kirchhoff Law
  • Classical Key Distribution
  • Person-Oriented Research
  • Machine Learning Algorithms
  • Artificial Neural Network
  • Directional Dependence Analysis
  • Statistical Package ROPstat
  • Configural Frequency Analysis
Research works
5.5k
fractional, since 1950
In the world top 10%
562
per year above
Top-10% rate
10.1%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+17%
the tick is no change
Largest producer
United States
40% of the 10 largest, 2022-now
Advanced Statistical Modeling Techniques

Which countries lead Advanced Statistical Modeling Techniques research?

By volume, the United States and China publish the most (345 and 114 works in 2022-now).

By volume, 2022-now

  1. 1 United States 345 works
  2. 2 China 114 works
  3. 3 India 104 works
  4. 4 Germany 88 works
  5. 5 Türkiye 45 works
  6. 6 Japan 37 works
  7. 7 Indonesia 33 works
  8. 8 Netherlands 33 works
  9. 9 United Kingdom 29 works
  10. 10 Italy 27 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.

United States: 40.3%China: 13.4%India: 12.2%Germany: 10.3%6 others listed: 23.9%40%largest
United States345 · 40.3%China114 · 13.4%India104 · 12.2%Germany88 · 10.3%6 others listed204 · 23.9%

Shares of the rows listed above, not of the whole node.

Which institutions lead Advanced Statistical Modeling Techniques research?

By volume in 2022-now, Christian-Albrechts-Universität zu Kiel publishes the most Advanced Statistical Modeling Techniques research, followed by University of North Carolina at Chapel Hill and Sapienza University of Rome.

Who are the leading researchers in Advanced Statistical Modeling Techniques?

The most-cited researchers publishing on Advanced Statistical Modeling Techniques include Robert John Tibshirani, Donald B. Rubin and Trevor Hastie.

  1. 1 Robert John Tibshirani United States 396k citations
  2. 2 Donald B. Rubin United States 301k citations
  3. 3 Trevor Hastie United States 301k citations
  4. 4 Ralph B. D’Agostino United States 255k citations
  5. 5 Peter M. Bentler United States 233k citations
  6. 6 Jerome H. Friedman United States 224k citations
  7. 7 Marko Sarstedt Germany 221k citations
  8. 8 Christian M. Ringle Germany 215k citations
  9. 9 David A. Kenny United States 198k citations
  10. 10 Jacob Cohen United States 195k citations

Ranked by citations received across their whole record, among researchers with at least three works on this topic.

What are the most cited papers in Advanced Statistical Modeling Techniques?

The most cited paper in Advanced Statistical Modeling Techniques is "Evaluating Structural Equation Models with Unobservable Variables and Measurement Error" (Claes Fornell, David F. Larcker, 1981), with 61,338 citations. Next come "Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach" (45,150) and "Coefficient Alpha and the Internal Structure of Tests" (44,025).

Most cited papers
#PaperReleasedCitations
1 Evaluating Structural Equation Models with Unobservable Variables and Measurement Error Claes Fornell, David F. Larcker · Journal of Marketing Research Feb 1981 61,338
2 Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach Andrew F. Hayes Open access 6 May 2013 45,150
3 Coefficient Alpha and the Internal Structure of Tests Lee J. Cronbach · Psychometrika Open access Sep 1951 44,025
4 Structural equation modeling in practice: A review and recommended two-step approach. James C. Anderson, David W. Gerbing · Psychological Bulletin May 1988 40,395
5 Structural equation modeling with AMOS: basic concepts, applications, and programming Barbara M. Byrne Nov 2000 18,093
All 99 most cited papers, with filters and sorting

Where is Advanced Statistical Modeling Techniques research done?

The largest centres of Advanced Statistical Modeling Techniques research in 2022-now are Beijing (China), Tokyo (Japan), Kiel (Germany) and Ankara (Türkiye).

Largest cities, 2022-now

  1. 1 BeijingChina 25 works
  2. 2 TokyoJapan 17 works
  3. 3 KielGermany 14 works
  4. 4 AnkaraTürkiye 13 works
  5. 5 New YorkUnited States 12 works
  6. 6 AmsterdamNetherlands 12 works
  7. 7 SeoulSouth Korea 11 works
  8. 8 ChennaiIndia 11 works
  9. 9 LondonUnited Kingdom 11 works
  10. 10 RomeItaly 11 works
See Advanced Statistical Modeling Techniques on the map

Where is the best place to study Advanced Statistical Modeling Techniques?

Among universities, judged by research, Christian-Albrechts-Universität zu Kiel, University of North Carolina at Chapel Hill and Sapienza University of Rome 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.

0%5%10%mean 10.575%fractional works in this field (log) →share of work in the world top 10% →Christian-Albrechts-…Texas A&M UniversitySapienza University …University of North …
above the meannear itbelow it

One dot per university in the first ten of the table below, at the default weights. The upper left is the interesting corner: small places doing unusually strong work.

Excellenceshare of its work in the world top 10%, 2022-now and all time averaged
40%
Specialisationhow much of its work is in this field, counted up to 10× the world share
10%
Sizeits output in this field, on a log scale
30%
Growthoutput growth, counted from -20% to +20%
10%
Internationalshare of its work with a co-author abroad
10%
Each slider sets a weight; the share it gets of the score is beside it.
#UniversityScoreTop 10%SpecialisationWorksGrowth
1Christian-Albrechts-Universität zu KielGermany 73.610.8%44.8×14 +191.8%
2University of North Carolina at Chapel HillUnited States 44.210.3%5.1×10 -36.5%
3Sapienza University of RomeItaly 19.310.5%7.3×9 -
4Texas A&M UniversityUnited States 17.210.7%10.2×9 -30.7%

Universities only. The score blends excellence (40%), size (30%), specialisation (10%), growth (10%), international reach (10%), 2022-now; growth compares 2018-21 with 2022-25 and counts up to +20%, since a jump from a small base is mostly noise.

Every institution in Advanced Statistical Modeling Techniques, country by country

Is Advanced Statistical Modeling Techniques research growing?

Output in 2022-2025 was 17% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Advanced Statistical Modeling Techniques.

still counting19801990200020102020
grewheldshrank

The same series as a ribbon: one cell per year, darker for more. The line above answers how much; this answers when.

Its share of all research

Growing output can still be a shrinking share: all of science grows. This is Advanced Statistical Modeling Techniques as a percentage of every work published that year, 0.0041% in 2024.

still counting0.0050%0.010%0.015%Advanced Statistical Modeling Techniques0.0054% in 202519801990200020102020

Fractional works of Advanced Statistical Modeling Techniques over all fractional works that year. How the balance of science has shifted.

How much of it reaches the world top 10%

Year by year.

still counting5%10%15%Advanced Statistical Modeling Techniques10.2% in 2025200020102020

Of each year's works in it, the share that reached the world's 10% most cited for their field and year. A field is the world for its own topics, so there is no other line to hold it against.

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.

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