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Topic · Statistics and Probability

Advanced Causal Inference Techniques

Advanced Causal Inference Techniques is a research topic within Statistics and Probability. Science Explorer counts 17k research works in it since 1950. 10.0% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on methods for causal inference in observational studies, with an emphasis on reducing the effects of confounding. It covers topics such as propensity score methods, matching methods, regression discontinuity, mediation analysis, instrumental variables, bias correction, and confounding control.

  • Causal Inference
  • Propensity Score
  • Observational Studies
  • Treatment Effects
  • Matching Methods
  • Regression Discontinuity
  • Mediation Analysis
  • Instrumental Variables
  • Bias Correction
  • Confounding Control
Research works
17k
fractional, since 1950
In the world top 10%
1.7k
per year above
Top-10% rate
10.0%
share of its works in the world top 10%
Growth, 2018-21 → 2022-25
+34%
the tick is no change
Largest producer
United States
53% of the 10 largest, 2022-now
Advanced Causal Inference Techniques

Which countries lead Advanced Causal Inference Techniques research?

By volume, the United States and China publish the most (2.1k and 471 works in 2022-now).

By volume, 2022-now

  1. 1 United States 2.1k works
  2. 2 China 471 works
  3. 3 United Kingdom 368 works
  4. 4 Germany 222 works
  5. 5 Canada 211 works
  6. 6 Japan 139 works
  7. 7 Netherlands 139 works
  8. 8 France 115 works
  9. 9 Australia 114 works
  10. 10 Italy 102 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: 53.2%China: 11.7%United Kingdom: 9.2%Germany: 5.5%6 others listed: 20.4%53%largest
United States2,136 · 53.2%China471 · 11.7%United Kingdom368 · 9.2%Germany222 · 5.5%6 others listed818 · 20.4%

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

Which institutions lead Advanced Causal Inference Techniques research?

By volume in 2022-now, Harvard University publishes the most Advanced Causal Inference Techniques research, followed by University of North Carolina at Chapel Hill and University of Michigan.

By volume, 2022-now

  1. 1 Harvard UniversityUnited States 91 works
  2. 2 University of North Carolina at Chapel HillUnited States 86 works
  3. 3 University of MichiganUnited States 46 works
  4. 4 University of PennsylvaniaUnited States 45 works
  5. 5 Stanford UniversityUnited States 44 works
  6. 6 University College LondonUnited Kingdom 38 works
  7. 7 Yale UniversityUnited States 38 works
  8. 8 Johns Hopkins UniversityUnited States 36 works
  9. 9 Duke UniversityUnited States 35 works
  10. 10 University of WashingtonUnited States 35 works

Who are the leading researchers in Advanced Causal Inference Techniques?

The most-cited researchers publishing on Advanced Causal Inference Techniques include David Moher, Douglas G. Altman and George Davey Smith.

  1. 1 David Moher Canada 898k citations
  2. 2 Douglas G. Altman United Kingdom 862k citations
  3. 3 George Davey Smith United Kingdom 435k citations
  4. 4 Walter Churchill Willett United States 411k citations
  5. 5 Mark J. Daly United States 403k citations
  6. 6 Robert John Tibshirani United States 396k citations
  7. 7 Julian P. T. Higgins United Kingdom 390k citations
  8. 8 Zulfiqar Ahmed Bhutta Pakistan 371k citations
  9. 9 Ronald C. Kessler United States 360k citations
  10. 10 John J.V. McMurray United Kingdom 349k 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 Causal Inference Techniques?

The most cited paper in Advanced Causal Inference Techniques is "The central role of the propensity score in observational studies for causal effects" (Paul R. Rosenbaum, Donald B. Rubin, 1983), with 31,609 citations. Next come "SPSS and SAS procedures for estimating indirect effects in simple mediation models" (17,445) and "A Proportional Hazards Model for the Subdistribution of a Competing Risk" (13,914).

Most cited papers
#PaperReleasedCitations
1 The central role of the propensity score in observational studies for causal effects Paul R. Rosenbaum, Donald B. Rubin · Biometrika Open access 1983 31,609
2 SPSS and SAS procedures for estimating indirect effects in simple mediation models Kristopher J. Preacher, Andrew F. Hayes · Behavior Research Methods, Instruments, & Computers Open access Nov 2004 17,445
3 A Proportional Hazards Model for the Subdistribution of a Competing Risk Jason P. Fine, Malcolm H. Ray · Journal of the American Statistical Association Jun 1999 13,914
4 An Introduction to Propensity Score Methods for Reducing the Effects of Confounding in Observational Studies Peter C. Austin · Multivariate Behavioral Research Open access 31 May 2011 12,403
5 Mediation in experimental and nonexperimental studies: New procedures and recommendations. Patrick E. Shrout, Niall P. Bolger · Psychological Methods 2002 11,037
All 95 most cited papers, with filters and sorting

Where is Advanced Causal Inference Techniques research done?

The largest centres of Advanced Causal Inference Techniques research in 2022-now are London (United Kingdom), New York (United States), Beijing (China) and Chapel Hill (United States). Among places with at least 20 works in it, it is an unusually large share of all research in Chapel Hill, Durham and New Haven.

Largest cities, 2022-now

  1. 1 LondonUnited Kingdom 133 works
  2. 2 New YorkUnited States 127 works
  3. 3 BeijingChina 100 works
  4. 4 Chapel HillUnited States 85 works
  5. 5 CambridgeUnited States 84 works
  6. 6 BostonUnited States 75 works
  7. 7 TokyoJapan 63 works
  8. 8 PhiladelphiaUnited States 62 works
  9. 9 SeattleUnited States 62 works
  10. 10 TorontoCanada 51 works

Where it is the local speciality

  1. Chapel HillUS · 85.5 works9.9×
  2. DurhamUS · 47.9 works8.5×
  3. New HavenUS · 43.6 works7.9×
  4. CambridgeUS · 84.2 works7.0×
  5. SeattleUS · 61.6 works6.9×
← less than its size predicts1×more →

Location quotient: how much more of its research is in Advanced Causal Inference Techniques than the world average.

See Advanced Causal Inference Techniques on the map

Where is the best place to study Advanced Causal Inference Techniques?

Among universities, judged by research, Harvard University, Stanford University and University College London 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%10%20%mean 17.07%fractional works in this field (log) →share of work in the world top 10% →University of Califo…Harvard UniversityStanford UniversityUniversity College L…
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
1Harvard UniversityUnited States 83.218.1%6.8×91 +1.4%
2Stanford UniversityUnited States 72.617.8%7.2×44 +24.4%
3University College LondonUnited Kingdom 72.016.5%5.7×38 +41.5%
4University of California, Los AngelesUnited States 69.620.0%5.1×24 +18.6%
5University of TorontoCanada 68.915.1%3.7×32 +28.2%
6London School of Hygiene & Tropical MedicineUnited Kingdom 67.219.1%28.6×19 -10.6%
7Boston UniversityUnited States 62.420.5%8.1×16 +21.0%
8Yale UniversityUnited States 61.814.2%8.4×38 +76.7%
9University of MichiganUnited States 61.612.1%7.2×46 +26.4%
10Karolinska InstitutetSweden 61.617.3%7.1×17 +51.3%

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 Causal Inference Techniques, country by country

Is Advanced Causal Inference Techniques research growing?

Output in 2022-2025 was 34% higher than in 2018-2021, peaking in 2025. The fastest-growing topics are Advanced Causal Inference 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 Causal Inference Techniques as a percentage of every work published that year, 0.016% in 2024.

still counting0.010%0.020%0.030%Advanced Causal Inference Techniques0.021% in 202519801990200020102020

Fractional works of Advanced Causal Inference 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 Causal Inference Techniques10.1% 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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