Alan Agresti

Statistics and Probability · 2000–2018

A researcher in the Science corpus: 13 papers; trusts 81 researchers and is trusted by 39 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 113 citations into it; #2,254 of 12,932 by trust here, #2,629 by citations
• Artificial Intelligence — 33 citations into it; #5,514 of 35,345 by trust here, #16,771 by citations
• Management Science and Operations Research — 17 citations into it
• Statistical Learning Theory — 8 citations into it
• Economics and Econometrics — 6 citations into it; #11,388 of 23,481 by trust here, #18,597 by citations
• Optimization & Training — 6 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Control and Systems Engineering — 5 citations into it

Whom Alan Agresti trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Daniel McFadden
2. Robert Tibshirani
3. M. Stone
4. L. A. Goodman
5. Philippe Huber
6. William S. Cleveland
7. Halbert White
8. Lars Peter Hansen
9. Chris Hans
10. C. Anderson‐Cook

Who trusts Alan Agresti overall

1. Maria Iannario
2. Gerhard E. Tutz
3. Matthijs J. Warrens
4. Jeroen K. Vermunt
5. Monty L. Lynn
6. F. Polzin
7. Andrea Romei
8. Salvatore Ruggieri
9. Christopher R. Bilder
10. F. W. Townes

Papers from Alan Agresti's perspective

Ordered by how strongly the researchers Alan Agresti trusts endorse each paper. Same corpus, a different order for every researcher.

1. Regression Shrinkage and Selection via the Lasso
2. Estimating the Dimension of a Model
3. Generalized Linear Models
4. Controlling the false discovery rate: a practical and powerful approach to multiple testing
5. Information Theory and an Extension of the Maximum Likelihood Principle
6. Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper
7. Addendum: Regularization and variable selection via the elastic net
8. The Elements of Statistical Learning
9. Generalized Additive Models
10. Spline Models for Observational Data

Their papers

• Simple and Effective Confidence Intervals for Proportions and Differences of Proportions Result from Adding Two Successes and Two Failures (2000) — 552 citations
• 2. Random-Effects Modeling of Categorical Response Data (2000) — 141 citations
• A Correlated Probit Model for Joint Modeling of Clustered Binary and Continuous Responses (2001) — 183 citations
• Random effect models for repeated measures of zero-inflated count data (2005) — 400 citations
• Modeling Clustered Ordered Categorical Data: A Survey (2001) — 108 citations
• Simple ways to interpret effects in modeling ordinal categorical data (2018) — 60 citations
• Foundations of Linear and Generalized Linear Models (2015) — 457 citations
• Analysis of Ordinal Categorical Data: Agresti/Analysis (2010) — 996 citations
• The analysis of ordered categorical data: An overview and a survey of recent developments (2005) — 180 citations
• Statistics: The Art and Science of Learning from Data (2005) — 307 citations
• Introduction to Generalized Linear Models (2003) — 47 citations
• Modeling Nonnegative Data with Clumping at Zero: A Survey (2002) — 188 citations
• Strategies for Modeling a Categorical Variable Allowing Multiple Category Choices (2001) — 63 citations