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Survey Sampling and Estimation Techniques

Survey Sampling and Estimation Techniques is a research topic within Statistics and Probability. Science Explorer counts 5.4k research works in it since 1950. 15.3% of them reached the world's top 10% most cited for their field and year.

This cluster of papers focuses on statistical methods and techniques for conducting surveys on sensitive topics, such as the Randomized Response Technique, List Experiments, and the use of auxiliary information in survey sampling. The papers cover various estimation methods, including ratio estimators, multivariate regression analysis, and item count techniques, while addressing issues like social desirability bias and measurement errors.

  • Randomized Response Technique
  • Sensitive Questions
  • Survey Sampling
  • Estimation Methods
  • List Experiments
  • Social Desirability Bias
  • Quantitative Randomized Response Models
  • Auxiliary Information
  • Stratified Sampling
  • Population Mean Estimation
Research works
5.4k
fractional, since 1950
In the world top 10%
831
per year above
Top-10% rate
15.3%
share of its works in the world top 10%
Growth, 2013–17 → 2018–22
+3%
the tick is no change

Which countries lead Survey Sampling and Estimation Techniques research?

By volume, India and the United States publish the most (226 and 137 works in 2022–2025).

By volume, 2022–2025

  1. 1 India 226 works
  2. 2 United States 137 works
  3. 3 Pakistan 99 works
  4. 4 Nigeria 67 works
  5. 5 Saudi Arabia 54 works
  6. 6 China 40 works
  7. 7 Germany 25 works
  8. 8 Thailand 21 works
  9. 9 United Kingdom 19 works
  10. 10 Türkiye 18 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.

India: 32.0%United States: 19.4%Pakistan: 14.1%Nigeria: 9.4%6 others listed: 25.1%32%largest
India226 · 32.0%United States137 · 19.4%Pakistan99 · 14.1%Nigeria67 · 9.4%6 others listed178 · 25.1%

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

Which institutions lead Survey Sampling and Estimation Techniques research?

By volume in 2022–2025, Banaras Hindu University publishes the most Survey Sampling and Estimation Techniques research, followed by Babasaheb Bhimrao Ambedkar University and Usmanu Danfodiyo University.

Who are the leading researchers in Survey Sampling and Estimation Techniques?

The most-cited researchers publishing on Survey Sampling and Estimation Techniques include Donald B. Rubin and Vinod Kumar Gupta.

  1. 1 Donald B. Rubin United States 4.7k citations
  2. 2 Vinod Kumar Gupta India 2.5k citations

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

Where is Survey Sampling and Estimation Techniques research done?

The largest centres of Survey Sampling and Estimation Techniques research in 2022–2025 are Lucknow (India), Islamabad (Pakistan), Kolkata (India) and Lahore (Pakistan). Among places with at least 20 works in it, it is an unusually large share of all research in Lucknow.

Largest cities, 2022–2025

  1. 1 Lucknow India 34 works
  2. 2 Islamabad Pakistan 23 works
  3. 3 Kolkata India 21 works
  4. 4 Lahore Pakistan 21 works
  5. 5 Riyadh Saudi Arabia 17 works
  6. 6 Bangkok Thailand 17 works
  7. 7 Jammu India 17 works
  8. 8 Varanasi India 16 works
  9. 9 New Delhi India 16 works
  10. 10 Sokoto Nigeria 14 works

Where it is the local speciality

  1. LucknowIN · 34.0 works41×
← less than its size predictsmore →

Location quotient: how much more of its research is in Survey Sampling and Estimation Techniques than the world average.

See Survey Sampling and Estimation Techniques on the map

Where is the best place to study Survey Sampling and Estimation Techniques?

Among universities, judged by research, Babasaheb Bhimrao Ambedkar University, Quaid-i-Azam University and Banaras Hindu University 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%20%40%mean 21.98%fractional works in this node (log) →share in the world top 10% →Babasaheb Bhimrao Ambedkar University: 15, 30.9%Quaid-i-Azam University: 9, 38.1%Banaras Hindu University: 16, 30.9%University of Malakand: 12, 21.9%Indian Institute of Technology Dhanbad: 13, 18.2%University of Lucknow: 11, 35.2%King Mongkut's University of Technology North Bangkok: 10, 21.0%Usmanu Danfodiyo University: 13, 9.6%Vikram University: 13, 3.9%University of KwaZulu-Natal: 10, 10.1%Quaid-i-Azam Univers…Babasaheb Bhimrao Am…Banaras Hindu Univer…University of Malakand
above the meannear itbelow it

One dot per university in the table below. The upper left is the interesting corner: small places doing unusually strong work.

#UniversityScoreTop 10%SpecialisationWorksGrowth
1 Babasaheb Bhimrao Ambedkar UniversityIndia 49.130.9%244.7×15
2 Quaid-i-Azam UniversityPakistan 49.038.1%64.6×9 +88.9%
3 Banaras Hindu UniversityIndia 48.630.9%38.1×16 +1.3%
4 University of MalakandPakistan 43.221.9%273.8×12
5 Indian Institute of Technology DhanbadIndia 42.718.2%71.2×13 +132.7%
6 University of LucknowIndia 35.935.2%101.9×11 -45.0%
7 King Mongkut's University of Technology North BangkokThailand 30.521.0%90.1×10
8 Usmanu Danfodiyo UniversityNigeria 28.99.6%209.0×13
9 Vikram UniversityIndia 24.33.9%772.5×13 +13.7%
10 University of KwaZulu-NatalSouth Africa 23.210.1%31.5×10

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 Survey Sampling and Estimation Techniques research growing?

Output in 2018–2022 was 3% higher than in 2013–2017, peaking in 2025. The fastest-growing topics are Survey Sampling and Estimation Techniques.

19801990200020102020
grewheldshrank

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.