UF-Statistics


Agresti pic

Alan Agresti
Distinguished Professor Emeritus

Department of Statistics
University of Florida
Gainesville, FL 32611-8545


E-MAIL: aa "at" stat "dot" ufl "dot" edu

I was employed by the University of Florida from 1972-2010. I have also had visiting professor positions at Harvard University (including fall semester each year 2008-2014), Imperial College (London), the London School of Economics, and shorter visiting positions at several universities including Florence and Padova (Italy), Hasselt (Belgium), Paris VII, Boston University, and Oregon State.

Honors

Book Information and Supplemental Files

Short Courses

I have taught short courses on categorical data analysis topics for many universities, professional organizations, conferences, and companies, mainly in Europe and the U.S. These range in length from half-day to a week, most commonly one or two days on topics such as "Modeling Ordinal Categorical Responses," "Analyzing Clustered Categorical Data," "Introduction to Categorical Data Analysis," "Discrete Data Analysis," and "Generalized Linear Modeling."

History of Statistics at UF

Click on UF Statistics to download the chapter on the history of the University of Florida Statistics Department, taken from the book Strength in Numbers: The Rising of Academic Statistics Departments in the U.S. edited by Alan Agresti and Xiao-Li Meng. See UF Stat documents for other historical documents, including pictures (unfortunately, not updated for some time).

Research and Publications

My primary research interests have been in categorical data analysis.

Books

  • Foundations of Linear and Generalized Linear Models, Wiley (2015).

  • Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., Springer (2012), co-edited with Xiao-Li Meng.

  • Statistics: The Art and Science of Learning from Data, 4th edition, Pearson (2017), with Chris Franklin and Bernhard Klingenberg.

  • Analysis of Ordinal Categorical Data, 2nd ed., Wiley (2010).

  • An Introduction to Categorical Data Analysis, 3rd ed., Wiley (2018).

  • Categorical Data Analysis, 3rd edition, Wiley (2013).

  • Statistical Methods for the Social Sciences, 5th edition, Pearson (2018) (4th edition 2009 with B. Finlay).

    • Some Articles

  • Bounds on the extinction time distribution of a branching process. Advances in Applied Probability, 6 (1974), 322-335. pdf file

  • On the extinction times of varying and random environment branching processes. Journal of Applied Probability, 12 (1975), 39-46. pdf file

  • The effect of category choice on some ordinal measures of association. Journal of the American Statistical Association, 71 (1976), 49-55.

  • Some exact conditional tests of independence for r x c cross-classification tables. (with D. Wackerly) Psychometrika, 42 (1977), 111-125. pdf file

  • Some considerations in measuring partial association for ordinal categorical data. Journal of the American Statistical Association, 72 (1977), 37-45.

  • A coefficient of multiple association based on ranks. Communications in Statistics, A6 (1977), 1341-1359.

  • Statistical analysis of qualitative variation. (with B. Agresti), Chapter 10, in Sociological Methodology (1978) ed. by K. F. Schuessler, Jossey-Bass Publ., 204-237.

  • Descriptive measures for rank comparisons of groups. Proceedings of the Social Statistics Section of the American Statistical Association, (1978), 585-590.

  • Exact conditional tests for cross-classifications: Approximation of attained significance level. (with D. Wackerly and J. Boyett), Psychometrika, 44 (1979), 75-83. pdf file

  • Measuring association and modelling relationships between interval and ordinal variables. (J. Schollenberger, A. Agresti, and D. Wackerly), Proceedings of the Social Statistics Section of the American Statistical Association, (1979), 624-626.

  • Generalized odds ratios for ordinal data. Biometrics, 36 (1980), 59-67. pdf file

  • A hierarchical system of interaction measures for multidimensional contingency tables. Journal of the Royal Statistical Society B, 43 (1981), 293-301.

  • Measures of nominal-ordinal association, Journal of the American Statistical Association, 76 (1981), 524-529. pdf file

  • Statistical fallacies. Encyclopedia of the Statistical Sciences, Vol. 3 (1983), John Wiley and Sons, 24-28.

  • Testing marginal homogeneity for ordinal categorical variables, Biometrics, 39, (1983), 505-510. pdf file

  • A survey of strategies for modelling cross-classifications having ordinal variables. Invited Essay Review in Journal of the American Statistical Association, 78 (1983), 184-198.

  • Association models for multidimensional cross-classifications of ordinal variables (with A. Kezouh), invited paper for issue on categorical data, Communications in Statistics, A12 (1983), 1261-1276.

  • A simple diagonals-parameter symmetry and quasisymmetry model, Statistics and Probability Letters, 1 (1983), 313-316. pdf file

  • The measurement of classification agreement: An adjustment to the Rand statistic for chance agreement (with L. Morey), Educational and Psychological Measurement, 44 (1984), 33-37.

  • Ordinal data. Encyclopedia of the Statistical Sciences, Vol. 6 (1985), John Wiley and Sons, 511-516.

  • Comparing mean ranks for repeated measures data (with J. Pendergast), Communications in Statistics, A15 (1986), 1417-1433. pdf file

  • A new model for ordinal pain data from a pharmaceutical study (with C. Chuang), Statistics in Medicine, 5 (1986), 15-20.

  • Applying R-squared type measures to ordered categorical data, Technometrics, 28 (1986), 133-138. pdf file

  • Models for the probability of concordance in cross-classification tables (with J. Schollenberger and D. Wackerly), Quality and Quantity (International Journal of Methodology), 21 (1987), 49-57. pdf file

  • Order-restricted score parameters in association models for contingency tables (with C. Chuang and A. Kezouh), Journal of the American Statistical Association, 82 (1987), 619-623.

  • Bayesian and maximum likelihood approaches to order-restricted inference for models for ordinal categorical data (with C. Chuang), pp. 6-27 in Advances in Order Restricted Statistical Inference, (1986), ed. by R. Dykstra, T. Robertson, and F.T. Wright, New York: Springer-Verlag.

  • An empirical investigation of some effects of sparseness in contingency tables (with M. Yang), Computational Statistics & Data Analysis, 5 (1987), 9-21.

  • A model for agreement between ratings on an ordinal scale, Biometrics, 44 (1988), 539-548.

  • Logit models for repeated ordered categorical response data, invited paper for Proceedings of 13th SAS Users Group Conference, (1988), 997-1005.

  • An agreement model with Kappa as parameter, Statistics and Probability Letters, 7 (1989), 271-273.

  • Model-based Bayesian methods for estimating cell proportions in cross-classification tables having ordered categories (with C. Chuang), Computational Statistics \& Data Analysis, 7 (1989), 245-258.

  • A tutorial on modeling ordered categorical response data, Psychological Bulletin, 105 (1989), 290-301.

  • A survey of models for repeated ordered categorical response data, Statistics in Medicine, 8 (1989), 1209-1224.

  • Exact inference for contingency tables with ordered categories (with C. Mehta and N. Patel), Journal of the American Statistical Association, 85 (1990), 453-458.

  • Analysis of sparse repeated categorical measurement data (with S. Lipsitz and J. B. Lang), SAS Users Group International Conference Proceedings, 1991, 1452-1460.

  • Parsimonious latent class models for ordinal variables, invited paper in Proceedings of 6th International Workshop on Statistical Modeling, (1991), 1-12, Utrecht, Netherlands.

  • Analysis of ordinal paired comparison data, Journal of the Royal Statistical Society C (Applied Statistics), 41 (1992), 287-297. pdf file

  • Loglinear modeling of pairwise interobserver agreement on a categorical scale (M. P. Becker and A. Agresti), Statistics in Medicine, 11 (1992), 101-114.

  • Comparing marginal distributions of large, sparse contingency tables (with S. Lipsitz and J. B. Lang), Computational Statistics and Data Analysis, 14 (1992), 55-73.

  • A survey of exact inference for contingency tables (with discussion), Statistical Science, 7 (1992), 131-177. pdf file

  • Quasi-symmetric latent class models, with application to rater agreement (with J. Lang), Biometrics, 49 (1993), 131-140. pdf file

  • Modeling patterns of agreement and disagreement, Statistical Methods in Medical Research, 1 (1992), 201-218.

  • Computing conditional maximum likelihood estimates for generalized Rasch models using simple loglinear models with diagonals parameters, Scandinavian Journal of Statistics, 20 (1993), 63-72.

  • Some empirical comparisons of exact, modified exact, and higher-order asymptotic tests of independence for ordered categorical variables (with J. Lang and C. Mehta), Communications in Statistics, Simulation and Computation, 22 (1993), 1-18.

  • A proportional odds model with subject-specific effects for repeated ordered categorical responses (with J. Lang), Biometrika, 80 (1993), 527-534. pdf file

  • Distribution-free fitting of logit models with random effects for repeated categorical responses, Statistics in Medicine, 12 (1993), 1969-1987.

  • Simultaneously modeling joint and marginal distributions of multivariate categorical responses (J. Lang and A. Agresti), Journal of the American Statistical Association, 89 (1994), 625-632.

  • Simple capture-recapture models permitting unequal catchability and variable sampling effort, Biometrics, 50, (1994), 494-500.

  • Logit models and related quasi-symmetric loglinear models for comparing responses to similar items in a survey, Sociological Methods and Research, 24 (1995), 68-95. pdf file

  • Improved exact inference about conditional association in three-way contingency tables (D. Kim and A. Agresti), Journal of the American Statistical Association, 90 (1995), 632-639.

  • Raking kappa: Describing potential impact of marginal distributions on measures of agreement (with A. Ghosh and M. Bini), Biometrical Journal, 37 (1995) 811-820.

  • Order-restricted tests for stratified comparisons of binomial proportions (with B. Coull), Biometrics, 52 (1996) 1103-1111.

  • Mantel--Haenszel--type inference for cumulative odds ratios (I-M. Liu and A. Agresti), Biometrics, 52 (1996) 1223-1234.

  • Logit models with random effects and quasi-symmetric loglinear models, pp. 3-12 in Statistical Modelling, Proceedings of the 11th International Workshop on Statistical Modelling (Orvieto, Italy, July 1996).

  • Connections between loglinear models and generalized Rasch models for ordinal responses, Chapter 20 in Applications of Latent Trait and Latent Class Models in the Social Sciences, pp. 209-218, edited by J. Rost and R. Langeheine, Berlin: Waxmann Munster, (1997).

  • Nearly exact tests of conditional independence and marginal homogeneity for sparse contingency tables (D. Kim and A. Agresti), Computational Statistics and Data Analysis, (1997), 24, 89-104.

  • A review of tests for detecting a monotone dose-response relationship with ordinal response data (with C. Chuang-Stein), Statistics in Medicine, (1997), 16, 2599-2618.

  • A model for repeated measurements of a multivariate binary response, Journal of the American Statistical Association (1997).

  • An empirical comparison of inference using order-restricted and linear logit models for a binary response (with B. Coull), Communications in Statistics, Simulation and Computation, (1998), 27, 147-166.

  • Evaluating agreement and disagreement among movie reviewers, Chance (1997) (with L. Winner). pdf file

  • Comment on article by Strawderman and Wells, Journal of the American Statistical Association, (1998), 93, 1307-1310.

  • Approximate is better than exact for interval estimation of binomial proportions, The American Statistician (1998) (with B. Coull). pdf file

  • Order-restricted inference for monotone trend alternatives in contingency tables Computational Statistics & Data Analysis (1998) (with B. Coull). pdf file

  • On logit confidence intervals for the odds ratio with small samples, Biometrics (1999).

  • The use of mixed logit models to reflect subject heterogeneity in capture-recapture studies, Biometrics (1999) (B. Coull and A. Agresti).

  • Modeling a categorical variable allowing arbitrarily many category choices, Biometrics (1999) (with I. Liu).

  • Modelling ordered categorical data: Recent advances and future challenges, Statistics in Medicine (1999).

  • Random effects modeling of multiple binary responses using the multivariate binomial logit-normal distribution, Biometrics (2000) (B. A. Coull and A. Agresti).

  • Strategies for comparing treatments on a binary response with multi-center data, Statistics in Medicine (2000) (with J. Hartzel). pdf file

  • Hierarchical Bayesian analysis of binary matched pairs data, Statistica Sinica (2000) (M. Ghosh, M. Chen, A. Ghosh, and A. Agresti).

  • Noninformative priors for one parameter item response models, Journal of Statistical Planning and Inference (2000) (M. Ghosh, M. Chen, A. Ghosh, and A. Agresti).

  • Challenges for categorical data analysis in the twenty-first century, in Statistics for the 21st Century, edited by C. R. Rao and G. J. Szekely, Marcel Dekker (2000).

  • Summarizing the predictive power of a generalized linear model, Statistics in Medicine (2000) (B. Zheng and A. Agresti) pdf file

  • Simple and effective confidence intervals for proportions and difference of proportions result from adding two successes and two failures, The American Statistician (2000) (with B. Caffo). pdf file

  • Random effects modeling of categorical response data, Sociological Methodology (2000) (A. Agresti, J. Booth, J. P. Hobert, and B. Caffo). pdf file

  • Describing heterogeneous effects in stratified ordinal contingency tables, with application to multi-center clinical trials, Computational Statistics & Data Analysis (2001) (J. Hartzel, I. Liu, and A. Agresti). pdf file

  • Strategies for modeling a categorical variable allowing multiple category choices, Sociological Methods and Research (2001) (A. Agresti and I. Liu).

  • Exact inference for categorical data: recent advances and continuing controversies, Statistics in Medicine (2001).

  • A correlated probit model for multivariate repeated measures of mixtures of binary and continuous responses, Journal of American Statistical Association (2001) (R.V. Gueorguieva and A. Agresti). pdf file

  • On small-sample confidence intervals for parameters in discrete distributions, Biometrics (2001) (A. Agresti and Y. Min). pdf file

  • Multinomial logit random effects models, Statistical Modelling (2001) (J. Hartzel, A. Agresti, and B. Caffo). pdf file

  • Modeling clustered ordered categorical data: A survey, International Statistical Review (2001) (A. Agresti and R. Natarajan).

  • Statistical issues in the 2000 U.S. Presidential election in Florida, University of Florida Journal of Law and Public Policy (Fall 2001 issue) (A. Agresti and B. Presnell). pdf file

  • Comment (with B. Coull) on article by Brown, Cai, and DasGupta. Statistical Science, (2001), 16, 117-120.

  • The analysis of contingency tables under inequality constraints, Journal of Statistical Planning and Inference (2002) (A. Agresti and B. A. Coull). pdf file

  • Measures of relative model fit, Computational Statistics and Data Analysis (2002) (A. Agresti and B. Caffo).

  • Unconditional small-sample confidence intervals for the odds ratio, Biostatistics (2002) (A. Agresti and Y. Min). pdf file

  • Modeling nonnegative data with clumping at zero: A survey, Journal of the Iranian Statistical Society (2002) (Y. Min and A. Agresti). pdf file

  • Links between binary and multi-category logit item response models and quasi-symmetric loglinear models, for special issue of Annales de la Faculte des Sciences de Toulouse Mathematiques, to honor retirement of Henri Caussinus, (2002). pdf file

  • On sample size guidelines for teaching inference about the binomial parameter in introductory statistics, unpublished manuscript by A. Agresti and Y. Min (2002). pdf file

  • The 2000 Presidential election in Florida: Misvotes, undervotes, overvotes, Statistical Science (2002) (A. Agresti and B. Presnell). pdf file

  • Dealing with discreteness: Making `exact' confidence intervals for proportions, differences of proportions, and odds ratios more exact, Statistical Methods in Medical Research (2003). pdf file

  • A class of generalized log-linear models with random effects, Statistical Modelling (2003) (B. A. Coull and A. Agresti). pdf file

  • Interview with Alan Agresti, conducted by Jackie Dietz, STATS (The Magazine for Students of Statistics) (2004). Word file

  • Examples in which misspecification of a random effects distribution reduces efficiency, Computational Statistics & Data Analysis (2004) (A. Agresti, P. Ohman, and B. Caffo). pdf file

  • Effects and noneffects of paired identical observations in comparing proportions with binary matched-pairs data, Statistics in Medicine (2004) (A. Agresti and Y. Min). pdf file

  • Improved confidence intervals for comparing matched proportions, Statistics in Medicine (2005) (A. Agresti and Y. Min). pdf file

  • Frequentist performance of Bayesian confidence intervals for comparing proportions in 2x2 contingency tables, Biometrics (2005) (A. Agresti and Y. Min). pdf file

  • Random effect models for repeated measures of zero-inflated count data, Statistical Modelling (2005) (Y. Min and A. Agresti). pdf file

  • The analysis of ordered categorical data: An overview and a survey of recent developments, invited discussion paper for the Spanish Statistical Journal, TEST (2005) (I. Liu and A. Agresti). pdf file

  • Multivariate tests comparing binomial probabilities, with application to safety studies for drugs, Applied Statistics (JRSS-C) (2005) (A. Agresti and B. Klingenberg). pdf file

  • Bayesian inference for categorical data analysis, Statistical Methods and Application (Journal of the Italian Statistical Society), (2005) (A. Agresti and D. Hitchcock). pdf file

  • Randomized confidence intervals and the mid-P approach, discussion of article by C. Geyer and G. Meeden, Statistical Science, (2005) (A. Agresti and A. Gottard). pdf file

  • Multivariate extensions of McNemar's test, Biometrics, (2006) (B. Klingenberg and A. Agresti). pdf file

  • Independence in multi-way contingency tables: S. N. Roy's breakthroughs and later developments, Journal of Statistical Planning and Inference, (2007) (A. Agresti and A. Gottard). pdf file

  • A class of ordinal quasi-symmetry models for square contingency tables, Statistics and Probability Letters, (2007) (M. Kateri and A. Agresti). pdf file

  • Reducing conservativism of exact small-sample methods of inference for discrete data, Computational Statistics and Data Analysis, (2007) (A. Agresti and A. Gottard). pdf file

  • Modeling and inference for an ordinal effect size measure, Statistics in Medicine, (2008) (E. Ryu and A. Agresti). pdf file

  • Simultaneous confidence intervals for comparing binomial parameters, Biometrics, (2008) (A. Agresti, M. Bini, B. Bertaccini, and E. Ryu). pdf file

  • A generalized regression model for a binary response, Statistics and Probability Letters, (2010) (M. Kateri and A. Agresti). pdf file

  • Pseudo-score confidence intervals for parameters in discrete statistical models, Biometrika, (2010) (A. Agresti and E. Ryu). pdf file

  • Score and pseudo score confidence intervals for categorical data analysis, invited article for Gary Koch festschrift, Statistics in Biopharmaceutical Research, (2011). pdf file

  • Quasi-symmetric graphical log-linear models, Scandinavian Journal of Statistics, (2011) (A. Gottard, G.M. Marchetti, and A. Agresti). pdf file

  • Statistics as an academic discipline, by A. Agresti and X.-L. Meng, Chapter 1 in Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., edited by A. Agresti and X.-L. Meng, (2012) Springer. pdf file

  • University of Florida Department of Statistics, by A. Agresti, W. Mendenhall III, and Richard Scheaffer. Chapter in Strength in Numbers: The Rising of Academic Statistics Departments in the U.S., edited by A. Agresti and X.-L. Meng, (2012) Springer. pdf file

  • Bayesian inference about odds ratio structure in ordinal contingency tables, (2013) (A. Agresti and M. Kateri), in special issue of Environmetrics to honor the memory of George Casella. pdf file

  • GEE for multinomial responses using a local odds ratios parameterization, Biometrics, (2013) (A. Touloumis, A. Agresti, and M. Kateri). pdf file

  • Some remarks on latent variable models in categorical data analysis, Communications in Statistics, Theory and Methods, (2014) (A. Agresti and M. Kateri), in special issue of invited contributions to the conference "Methods and Models on Latent Variables" held in Naples, Italy in May 2012. pdf file

  • Two Bayesian/frequentist challenges for categorical data analyses, Metron, (2014), in special issue of invited contributions to the conference "Recent Advances in Statistical Inference: Theory and Case Studies" held in Padova, Italy in March 2013.

  • Ordinal effect size measures for group comparisons in models, (A. Agresti and M. Kateri), (2015), in proceedings of International Workshop on Statistical Modelling in Linz, Austria.

  • Categorical regularization: Discussion of article by Tutz and Gertheiss, Statistical Modelling, (2016).

  • Ordinal probability effect measures for group comparisons in multinomial cumulative link models, (A. Agresti and M. Kateri), Biometrics (2017).

  • Simple effect measures for interpreting models for ordinal categorical data, (A. Agresti and C. Tarantola), pp. 252-257 in Proceedings of the 32nd International Workshop on Statistical Modelling, Groningen, Netherlands, 2017.

  • Simple effect measures for interpreting models for ordinal categorical data (A. Agresti and C. Tarantola), Statistica Neerlandica (2018) . pdf file
    • pdf file of appendix with supplementary R functions

  • Some issues in generalized linear modeling, (2019), in Springer proceedings of International Workshop on Matrices and Statistics, Funchal, Portugal, June 2016.

  • The class of CUB models: statistical foundations, inferential issues and empirical evidence, comments on article by D. Piccolo and R. Simone (A. Agresti and M. Kateri), Statistical Methods and Applications (SMA) (2019).

  • Simple ways to interpret effects in modeling binary data, (A. Agresti, C. Tarantola, and R. Varriale), 2019.

    • Old home pages for courses at UF

    Other Information

    The University of Florida Statistics Department home page

    Here is a seminar (in mp4 format) on the

    Agresti pic8 Participants at workhop in my honor, Florence Italy, September 18, 2019. "Grazie mille ad Anna Gottard per aver organizzato questo meraviglioso evento." Here is the program about the Florence workshop.

    Agresti pic6 From my Italian citizenship ceremony in Ferrazzano (2017)

    Agresti pic7 European Statistics research colleagues and dear friends, from my Italian citizenship ceremony (2017)

    My roots (and two of my favorite spots on earth)

    Agresti pic5 Ferrazzano, Molise, Italy (la citta` di mia nonna italiana)

    Agresti pic3 Ferrazzano, Molise, Italy

    Agresti pic2 Ferrazzano, Molise, Italy

    Agresti pic2a Campobasso (Ferrazzano is 5 km south of this capital city of Molise, Italy

    Agresti pic1 Forest of Dean, Gloucestershire, England (the land of my British grandparents)

    The picture at the top of my home page was taken by Jacki Levine in the Forest of Dean, Gloucestershire, UK, among the May bluebells.

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