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Mathematics
USA
2026

D-Index & Metrics

Mathematics

D-Index
74
Citations
70105
World Ranking
206
National Ranking
117

Research.com Recognitions

  • 2026 - Research.com Mathematics in United States Leader Award
  • 2025 - Research.com Mathematics in United States Leader Award
  • 1990 - Fellow of the American Statistical Association (ASA)

Overview

Alan Agresti is affiliated with the University of Florida in the United States. Their research spans several key areas within mathematics and computer science, with a strong focus on statistics and probability as the primary subfield. The body of work demonstrates significant contribution to statistical methods, Bayesian inference, and data analysis.

The main fields of study for Alan Agresti include:

  • Mathematics
  • Computer Science

The primary subfields explored by Agresti are:

  • Statistics and Probability
  • Artificial Intelligence
  • Computer Networks and Communications
  • General Agricultural and Biological Sciences

The main topics of their research encompass:

  • Statistical Methods and Bayesian Inference
  • Advanced Statistical Methods and Models
  • Statistical Methods and Inference
  • Statistics Education and Methodologies
  • Bayesian Modeling and Causal Inference
  • Probability and Statistical Research
  • Data Analysis with R

Alan Agresti has published in several academic venues, reflecting a range of statistical science topics. Notable publication venues include:

  • Brazilian Journal of Probability and Statistics
  • Scandinavian Journal of Statistics
  • Journal of Quantitative Economics
  • Statistical Modelling
  • Journal of the American Statistical Association

Recent papers feature detailed explorations in statistical science and categorical data inference. Selected works include:

  • The foundations of statistical science: A history of textbook presentations (2021, Brazilian Journal of Probability and Statistics)
  • A historical overview of textbook presentations of statistical science (2023, Scandinavian Journal of Statistics)
  • A Review of Score-Test-Based Inference for Categorical Data (2022, Journal of Quantitative Economics)
  • Reflections on Murray Aitkin's contributions to nonparametric mixture models and Bayes factors (2021, Statistical Modelling)
  • Confidence Intervals for Discrete Data in Clinical Research (2023, Journal of the American Statistical Association)

Frequent co-authors in their research collaborations include:

  • Claudia Tarantola
  • Roberta Varriale
  • Maria Kateri
  • Sabrina Giordano
  • Anna Gottard

In recognition of their work, Alan Agresti was named Fellow of the American Statistical Association in 1990.

Best Publications

  • Categorical data analysis

    Alan Agresti

  • An introduction to categorical data analysis

    Alan Agresti

  • Statistical Methods for the Social Sciences

    Alan Agresti;Barbara Finlay

  • Approximate is Better than “Exact” for Interval Estimation of Binomial Proportions

    Alan Agresti;Brent A. Coull

  • Analysis of ordinal categorical data

    Alan Agresti

  • A Survey of Exact Inference for Contingency Tables

    Alan Agresti

  • Foundations of Linear and Generalized Linear Models

    Alan Agresti

  • Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures

    Alan Agresti;Brian Caffo

  • Categorical Data Analysis

    Unknown

  • Random effect models for repeated measures of zero-inflated count data:

    Yongyi Min;Alan Agresti

  • Statistical Analysis of Qualitative Variation

    Alan Agresti;Barbara F. Agresti

  • The analysis of ordered categorical data: An overview and a survey of recent developments

    Ivy Liu;Alan Agresti

  • Summarizing the predictive power of a generalized linear model.

    Beiyao Zheng;Alan Agresti

  • Simultaneously Modeling Joint and Marginal Distributions of Multivariate Categorical Responses

    Joseph B. Lang;Alan Agresti

  • Statistical models for ordinal variables

    Alan Agresti;Clifford C. Clogg;Edward S. Shihadeh

  • Random-Effects Modeling of Categorical Response Data

    Alan Agresti;James G Booth;James P Hobert;Brian S Caffo

  • Multinomial logit random effects models

    Jonathan Hartzel;Alan Agresti;Brian S Caffo

  • Introduction to Generalized Linear Models

    Alan Agresti

  • Statistics: The Art and Science of Learning from Data

    Alan Agresti;Christine A. Franklin

  • Categorical Data Analysis.

    G. J. G. Upton;A. Agresti

  • Categorical Data Analysis.

    Dennis Lendrem;A. Agresti

  • Analysis of Ordinal Categorical Data.

    R. L. Plackett;A. Agresti

  • Teacher's Corner Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures

    Alan Agresti;Brian Caffo

Frequent Co-Authors

Brent A. Coull
Brent A. Coull Harvard University
Myles Hollander
Myles Hollander Florida State University
Malay Ghosh
Malay Ghosh University of Florida
Roderick J. A. Little
Roderick J. A. Little University of Michigan–Ann Arbor
Ming-Hui Chen
Ming-Hui Chen University of Connecticut
Stuart R. Lipsitz
Stuart R. Lipsitz Brigham and Women's Hospital
James M. Boyett
James M. Boyett St. Jude Children's Research Hospital
Jeffrey S. Simonoff
Jeffrey S. Simonoff New York University
Mark S. Handcock
Mark S. Handcock University of California, Los Angeles
Leslie C. Morey
Leslie C. Morey Texas A&M University

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