H-Index & Metrics Best Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Social Sciences and Humanities D-index 80 Citations 64,609 177 World Ranking 103 National Ranking 51

Research.com Recognitions

Awards & Achievements

2010 - Member of the National Academy of Sciences

2004 - Fellow of the American Association for the Advancement of Science (AAAS)

1998 - Fellow of the American Academy of Arts and Sciences

Overview

What is he best known for?

The fields of study he is best known for:

  • Statistics
  • Law
  • Social science

His scientific interests lie mostly in Econometrics, Causal inference, Statistical model, Variables and Algorithm. His research on Econometrics also deals with topics like

  • Event that intertwine with fields like International relations and Inefficiency,
  • Estimator that connect with fields like Poisson regression. His Causal inference research includes elements of Parametric statistics, Parametric model, Balance, Matching and Preprocessor.

His Statistical model research is multidisciplinary, incorporating perspectives in Empirical evidence, Simple, Duration, Interpretation and Data science. His Variables research is multidisciplinary, relying on both Logistic regression, Rare events and Missing data. Gary King combines subjects such as Software and Monotonic function with his study of Algorithm.

His most cited work include:

  • Designing Social Inquiry: Scientific Inference in Qualitative Research (3705 citations)
  • Making the Most of Statistical Analyses: Improving Interpretation and Presentation (2527 citations)
  • Logistic Regression in Rare Events Data (2441 citations)

What are the main themes of his work throughout his whole career to date?

The scientist’s investigation covers issues in Econometrics, Inference, Politics, Statistical model and Causal inference. His Econometrics research incorporates elements of Event, Statistics, Variables, Estimator and Redistricting. His Inference study integrates concerns from other disciplines, such as Ecology and Aggregate data.

He has researched Politics in several fields, including Positive economics, Public relations and Political economy. Statistical model is often connected to Aggregate in his work. His work in Causal inference addresses issues such as Matching, which are connected to fields such as Algorithm.

He most often published in these fields:

  • Econometrics (17.36%)
  • Inference (10.36%)
  • Politics (9.84%)

What were the highlights of his more recent work (between 2013-2021)?

  • Internet privacy (3.11%)
  • Inference (10.36%)
  • Causal inference (8.55%)

In recent papers he was focusing on the following fields of study:

Gary King mainly investigates Internet privacy, Inference, Causal inference, Social media and Interactive Learning. His Internet privacy study incorporates themes from Replication, Subject and Big data. His study in Inference is interdisciplinary in nature, drawing from both Identification, Statistical inference, Econometrics, Aggregate data and Ground truth.

The study incorporates disciplines such as Balance, Matching, Preprocessor, Control and Randomized experiment in addition to Causal inference. His study focuses on the intersection of Social media and fields such as Censorship with connections in the field of China, Reverse engineering and Collective action. His Government study combines topics from a wide range of disciplines, such as Politics and Public relations.

Between 2013 and 2021, his most popular works were:

  • The Parable of Google Flu: Traps in Big Data Analysis (1424 citations)
  • How the Chinese Government Fabricates Social Media Posts for Strategic Distraction, Not Engaged Argument (250 citations)
  • Comment on “Estimating the reproducibility of psychological science” (235 citations)

In his most recent research, the most cited papers focused on:

  • Statistics
  • Law
  • Social science

Gary King spends much of his time researching Social media, Causal inference, Big data, Internet privacy and Public relations. The various areas that he examines in his Causal inference study include Inefficiency, Pruning, Matching, Statistical inference and Frequentist inference. His Matching research is multidisciplinary, incorporating elements of Preprocessor, Propensity score matching, Algorithm, Randomized experiment and Blocking.

His work carried out in the field of Big data brings together such families of science as Estimation and Transparency. Gary King has researched Internet privacy in several fields, including Observational methods in psychology, Collective action, World Wide Web and Interface. Gary King has included themes like Government, Argument and Communism, Politics in his Public relations study.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Designing Social Inquiry: Scientific Inference in Qualitative Research

Gary King;Robert O. Keohane;Sidney Verba.
(1994)

13363 Citations

Making the Most of Statistical Analyses: Improving Interpretation and Presentation

Gary King;Michael Tomz;Jason Wittenberg.
American Journal of Political Science (2000)

4358 Citations

Logistic Regression in Rare Events Data

Gary King;Langche Zeng.
Political Analysis (2001)

4192 Citations

Matching as Nonparametric Preprocessing for Reducing Model Dependence in Parametric Causal Inference

Daniel E. Ho;Kosuke Imai;Gary King;Elizabeth A. Stuart.
Political Analysis (2007)

3794 Citations

Computational Social Science

David M. Lazer;Alex Pentland;Lada Adamic;Sinan Aral;Sinan Aral.
Science (2009)

3489 Citations

Analyzing Incomplete Political Science Data: An Alternative Algorithm for Multiple Imputation

Gary King;James Honaker;Anne Joseph;Kenneth Scheve.
American Political Science Review (2001)

2541 Citations

The Parable of Google Flu: Traps in Big Data Analysis

David Lazer;David Lazer;Ryan Kennedy;Ryan Kennedy;Ryan Kennedy;Gary King;Alessandro Vespignani;Alessandro Vespignani.
Science (2014)

2381 Citations

Amelia II: A Program for Missing Data

James Honaker;Gary King;Matthew Blackwell.
Journal of Statistical Software (2011)

2376 Citations

MatchIt: Nonparametric Preprocessing for Parametric Causal Inference

Daniel E. Ho;Kosuke Imai;Gary King;Elizabeth A. Stuart.
Journal of Statistical Software (2011)

2330 Citations

Causal Inference without Balance Checking: Coarsened Exact Matching

Stefano M. Iacus;Gary King;Giuseppe Porro.
Political Analysis (2012)

2329 Citations

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