Statistics the Art and Science of Learning From Data 4th Edition by Agrestifranklin

UF-Statistics

I was employed past the University of Florida from 1972-2010. I have also had visiting professor positions at Harvard Academy (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 7, Boston University, and Oregon Land. I have taught short courses in about 35 countries, such as at various universities each year since 1991 in Italia, where I became a denizen in 2017 to supplement my American citizenship. Details are in my CV.

Honors

Honorary doctorate, De Montfort Academy (Leicester, U.1000.), 1999
Statistician of the Year, Chicago chapter of American Statistical Association, 2003
Recipient of the first Herman Callaert Leadership Laurels in Statistical Education and Dissemination, Hasselt University, Diepenbeek, Belgium, 2004
Beau, American Statistical Association, 1990
Fellow, Constitute of Mathematical Statistics, 2008
University of Florida Distinguished Professor, 2000-2010
University of Florida Research Foundation (UFRF) Professorship, 1997-2000
Excellence in Continuing Education Honor from American Statistical Clan, 2002
36th Annual Allen T. Craig lecturer, Academy of Iowa, 2006
Categorical Information Analysis & Friends workshop in my laurels, University of Firenze, Italy, 2019
Keynote lectures at conferences include Swiss Statistical Gild (1992), French Biometric Society (1992), Conference on Statistical Issues in Biopharmaceutical Environments (1999) in the UK, Army Conference on Applied Statistics (2002), CDC almanac awards coming together (2003), Applied Statistics in Republic of ireland (2004), Hawaii International Conference on Statistics, Mathematics, and Related Fields (2004), International Social club of Clinical Biostatistics (2005) in Republic of hungary, CompStat (2006) in Italy, Applied Statistics (2007) in Slovenia, Royal Statistical Order (2008) in UK, Colombian Statistics Symposium (2012), Portuguese-Galician Biometry Meeting (2013), New England Statistics Symposium (2014), and invited lectures and curt courses in well-nigh 35 countries

Book Information and Supplemental Files

1. The textbook DS cover Foundations of Statistics for Data Scientists, with R and Python , written with Maria Kateri, has been published in November 2021 by CRC Press. Designed as a textbook for an introduction to mathematical statistics for students preparation to become data scientists, the volume provides an in-depth presentation of the topics in statistical science with which any data scientist should be familiar, including probability distributions, descriptive and inferential statistical methods, and linear modelling. Compared to traditional math stat textbooks, however, the book has less accent on probability theory and more emphasis on using software to implement statistical methods and to acquit simulations to illustrate key concepts. All statistical analyses in the volume employ R software, with an appendix showing the same analyses with Python. The volume too introduces mod topics that do not unremarkably appear in mathematical statistics texts only are highly relevant for data scientists, such equally Bayesian inference, generalized linear models for non-normal responses (eastward.grand., logistic regression and Poisson loglinear models), and regularized model fitting. It contains nearly 500 exercises. The book's website has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.

ii. The book

An Introduction to Categorical Data Analysis, (Wiley, 2019) was recently published in its 3rd edition. This new edition shows how to practice all analyses using R software and add some new cloth (e.k., Bayesian methods, nomenclature and smoothing). This volume, which presents a nontechnical introduction to topics such as logistic regression, is a lower-technical-level and shorter version of the "Categorical Data Analysis" text mentioned above. I've constructed a website for these texts that provides information about the use of Software for Chiselled Data Analysis such as SAS, R and S-Plus, SPSS, Stata, and StatXact. Data files from the text are at data files for Intro CDA. They are also available at a Github site for CDA data files and at the Wiley companion website for Intro CDA. For some data files from the 2nd edition, click on data files for Intro CDA. For SAS files containing information sets from the 2nd edition, click on SAS information sets for Intro CDA. Here are some corrections for the 1st edition of this book, a pdf file of corrections for the 2nd edition, and a pdf file of corrections for the 3rd edition. For those who apply R, a very useful and helpful R language compendium has been prepared by Professor Raymond Balise. Containing code and formulas to accompany this book, it tin be found at Balise R compendium for Intro CDA. Its Github project repository is public at Balise Github R repository for Intro CDA.

3. The text
Foundations of Linear and Generalized Linear Models, published by Wiley in Feb 2015, presents an overview of the most usually used statistical models past discussing the theory underlying the models and showing examples using R software. The book begins with the fundamentals of linear models, such as showing how least squares projects the information onto a model vector subspace and orthogonal decompositions of the data yield comparisons of models. The book then covers the theory of generalized linear models, with chapters on binomial and multinomial logistic regression for categorical data and Poisson and negative binomial loglinear models for count information. The book also introduces quasi-likelihood methods (such as generalized estimating equations), linear mixed models and generalized linear mixed models with random furnishings for clustered correlated information, Bayesian linear and generalized linear modeling, and regularization methods for high-dimensional information. The book has more than than 400 exercises. The book's website contains supplementary information, including data sets and corrections. Here is an interview about the book in the Wiley publication "Statistics Views." Here is a book review in the journal Biometrics,a volume review in Biometrical Journal, and some reviews at Amazon.

iv. The book Strength in Numbers

Strength in Numbers: The Ascent of Academic Statistics Departments in the U.S., co-edited with Xiao-Li Meng, has been published by Springer (2012). This book has a chapter for each of virtually xl Statistics and Biostatistics departments founded in the U.Due south. by the mid-1960s, describing the development of those departments and the kinesthesia and students who worked in them. Included are about 200 historical photos. See the Springer site for other details.

5. The text Categorical Data Analysis, 3rd Edition
Chiselled Data Assay, 3rd Edition

is in its third edition (Wiley, 2013). I've synthetic a Website for Categorical Data Analysis that provides datasets used for examples, solutions to some exercises, information about using R, SAS, Stata, and SPSS software for conducting the analyses in the text, a list of some typos and errors, and powerpoint slides. For users of R, Prof. Charles Geyer has prepared a CatDataAnalysis bundle for CDA at CRAN, with data files used in text examples and exercises. He also has a website with notes on CDA for the course he has taught at the University of Minnesota on categorical data analysis, with 1 section dealing with infinite ML estimates in canonical link models. Here is an interview that the Wiley publication "Statistics Views" conducted with me to mark the publication of the new edition. A website for 2d edition has some material for the 2nd edition. Dr. Laura Thompson has prepared a detailed transmission on the use of R or S-Plus to conduct all the analyses in the 2nd edition. Here is a copy of this excellent resources: Laura Thompson R and Due south manual for CDA.

vi. The text Analysis of Ordinal Categorical Data
Assay of Ordinal Categorical Information

(Wiley, 1984) has been revised, and the 2d edition was published in 2010. My ordinal categorical website contains (1) data sets for some examples in the class of SAS programs for conducting the analyses, (2) examples of the employ or R for plumbing equipment diverse ordinal models, (iii) examples of the utilise of Joe Lang'south mph.fit R role for various analyses in the book that are not easily conducted with SAS, Stata, SPSS, and standard functions in R, and (4) corrections of errors in early printings of the book (Please ship me whatsoever that y'all notice). Hither is the video for a half-mean solar day course I taught in 2020 for the Harvard School of Public Health on Modeling Ordinal Chiselled Data.

7. The text >
Statistics: The Fine art and Science of Learning from Data (5th edition, Pearson, 2021) was written with Christine Franklin of the Academy of Georgia and Bernhard Klingenberg of Williams College. Professor Klingenberg has developed a wonderful fix of applets and other resources for teaching from the volume (see Art of Stat ). This text is designed for a one-term or two-term undergraduate course or a loftier schoolhouse AP form on an introduction to statistics, presented with a conceptual approach. The link Table of Contents has a Table of Contents and information about the volume. Many supplemental materials are bachelor from Pearson, including an annotated instructor's edition, a lab workbook, videotaped lectures, and software supplements. Contact Ms. Suzanna Bainbridge, the Acquisitions Editor for Statistics at Pearson Educational activity, for details (suzanna.bainbridge@Pearson.com). An Italian translation of the 3rd edition is now available, cheers to Giuseppe Espa, Rocco Micciolo, Diego Giuliani and Maria Michela Dickson at the University of Trento.

viii. The volume

Statistical Methods for the Social Sciences, (5th edition, Pearson, 2018; 4th edition, by A. Agresti and B. Finlay, published 2009) is designed for a two-semester sequence. The book begins with the basics of statistical description and inference, and the second half concentrates on regression methods, including multiple regression, ANOVA and repeated measures ANOVA, analysis of covariance, logistic regression, and generalized linear models. The new edition adds R and Stata for software examples too equally introductions to new methodology such as multiple imputation for missing data, random effects modeling including multilevel models, robust regression, and the Bayesian approach to statistical inference. For applets used in some examples and exercises of the new edition, get to applets. These were designed by Bernhard Klingenberg for the text "Statistics: The Art and Science of Learning from Data" (4th and 5th ed.) by Agresti, Franklin, and Klingenberg. The book's website contains supplementary information, including data sets and corrections. Special directories also have data files in Stata format and in SPSS format. Some years agone, Jeffrey Arnold of the U of Washington kindly set up a R packet at CRAN for R users to exist able to access the datasets used in the 4th edition of this text. See R data files. He has also put the data files at a GitHub site, data files at GitHub. For examples of the utilise of the software Stata for various analyses for examples in the 4th edition of this text, see the useful site set by the UCLA Statistical Computing Middle. Thanks to Margaret Ross Tolbert for the cover art for the 5th edition. Margaret is an incredibly talented artist who has helped draw attention to the beauty but environmental deposition of the springs in north-central Florida (see world wide web.margaretrosstolbert.com). I am also pleased to report (due to my partial Italian heritage) that there is as well an Italian version of the first ten chapters of the 4th edition of this book (Statistica per le Scienze Sociali) and of the entire book (Metodi Statistici di Base eastward Avanzati per le scienze sociali) published past Pearson, and in that location is also a Portuguese version -- meet "Metodos Estatisticos para as Ciencas Socias" at Portuguese SMSS -- and a Chinese version, and it is beingness translated into Castilian. I accept developed Powerpoint files for lectures from Chapters 1-12 of this text that are available to instructors using this text. (Capacity 1-7 of these have also been translated into Castilian by Norma Leyva of Universidad Iberoamericana in United mexican states.) Please contact me for details. Finally, here is a link to a workshop held by the Department of Sociology, Oxford University, in 2012 that discussed issues in the teaching of quantitative methods to social scientific discipline students.

Short Courses

I have taught brusque courses on chiselled data analysis topics for many universities, professional person organizations, conferences, and companies, mainly in Europe and the U.South. These range in length from half-day to a calendar week, nigh normally one or two days on topics such every bit "Modeling Ordinal Chiselled Responses," "Analyzing Clustered Categorical Data," "Introduction to Categorical Data Analysis," "Detached Data Analysis," and "Generalized Linear Modeling." Here is the video for a one-half-day course I taught in 2020 for the Harvard School of Public Health on Modeling Ordinal Categorical Data.

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 Rise of Academic Statistics Departments in the U.Southward. edited by Alan Agresti and Xiao-Li Meng. See UF Stat documents for other historical documents, including pictures (unfortunately, not updated for some time).

Inquiry and Publications

(Details are in my CV.) My master research interests have been in chiselled information analysis.

Books

Foundations of Statistics for Data Scientists, with R and Python, with Maria Kateri, CRC Press (2021).

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 Information, fifth edition, Pearson (2021), with Chris Franklin and Bernhard Klingenberg.

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

An Introduction to Chiselled Information Analysis, 3rd ed., Wiley (2019).

Categorical Information Analysis, third 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, half-dozen (1974), 322-335. pdf file

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

The effect of category selection 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 chiselled information. 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. past Grand. F. Schuessler, Jossey-Bass Publ., 204-237.

Descriptive measures for rank comparisons of groups. Proceedings of the Social Statistics Department 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 information. Biometrics, 36 (1980), 59-67. pdf file

A hierarchical arrangement 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.

Clan 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 unproblematic diagonals-parameter symmetry and quasisymmetry model, Statistics and Probability Messages, ane (1983), 313-316. pdf file

The measurement of classification agreement: An aligning to the Rand statistic for run a risk agreement (with Fifty. 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.

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

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

Applying R-squared blazon 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 Periodical of Methodology), 21 (1987), 49-57. pdf file

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

Bayesian and maximum likelihood approaches to gild-restricted inference for models for ordinal categorical information (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 furnishings of sparseness in contingency tables (with 1000. Yang), Computational Statistics & Data Analysis, v (1987), 9-21.

A model for agreement betwixt ratings on an ordinal calibration, 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, vii (1989), 271-273.

Model-based Bayesian methods for estimating jail cell proportions in cross-nomenclature tables having ordered categories (with C. Chuang), Computational Statistics \& Information 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, eight (1989), 1209-1224.

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

Assay of sparse repeated categorical measurement data (with S. Lipsitz and J. B. Lang), SAS Users Grouping International Briefing 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 information, Journal of the Majestic Statistical Social club 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 big, 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 understanding (with J. Lang), Biometrics, 49 (1993), 131-140. pdf file

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

Calculating provisional maximum likelihood estimates for generalized Rasch models using simple loglinear models with diagonals parameters, Scandinavian Journal of Statistics, xx (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-xviii.

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

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

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

pdf file

Simple capture-recapture models permitting diff catchability and variable sampling endeavor, Biometrics, l, (1994), 494-500.

pdf file

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 almost conditional association in three-style contingency tables (D. Kim and A. Agresti), Periodical of the American Statistical Association, 90 (1995), 632-639.

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

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

pdf file

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

Logit models with random furnishings and quasi-symmetric loglinear models, pp. 3-12 in Statistical Modelling, Proceedings of the 11th International Workshop on Statistical Modelling (Orvieto, Italian republic, 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).

Almost exact tests of conditional independence and marginal homogeneity for sparse contingency tables (D. Kim and A. Agresti), Computational Statistics and Information 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 Clan (1997), 92, 315-321.

pdf file

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

Evaluating understanding and disagreement amidst movie reviewers, Chance (1997) (with L. Winner). pdf file

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

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

Guild-restricted inference for monotone tendency 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 reverberate 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 information: 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) (Thou. Ghosh, G. Chen, A. Ghosh, and A. Agresti).

Noninformative priors for one parameter particular response models, Journal of Statistical Planning and Inference (2000) (One thousand. 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 effect from calculation two successes and two failures, The American Statistician (2000) (with B. Caffo). pdf file

Random effects modeling of chiselled response information, 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 chiselled variable allowing multiple category choices, Sociological Methods and Research (2001) (A. Agresti and I. Liu).

Verbal inference for categorical data: recent advances and standing 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 conviction 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 information: A survey, International Statistical Review (2001) (A. Agresti and R. Natarajan). pdf file

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

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

The assay 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 Assay (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 naught: A survey, Journal of the Iranian Statistical Gild (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 consequence of Annales de la Faculte des Sciences de Toulouse Mathematiques, to honor retirement of Henri Caussinus, (2002). pdf file

On sample size guidelines for instruction 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 than 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 furnishings 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 result models for repeated measures of zero-inflated count data, Statistical Modelling (2005) (Y. Min and A. Agresti). pdf file

The assay of ordered categorical information: An overview and a survey of recent developments, invited give-and-take paper for the Spanish Statistical Journal, Exam (2005) (I. Liu and A. Agresti). pdf file

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

Bayesian inference for chiselled data analysis, Statistical Methods and Application (Periodical of the Italian Statistical Club), (2005) (A. Agresti and D. Hitchcock). pdf file

Randomized confidence intervals and the mid-P approach, word 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-style contingency tables: Southward. 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 detached information, Computational Statistics and Information 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 comparison binomial parameters, Biometrics, (2008) (A. Agresti, Chiliad. Bini, B. Bertaccini, and E. Ryu). pdf file

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

Pseudo-score confidence intervals for parameters in detached 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 Enquiry, (2011). pdf file

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

Statistics every bit an academic discipline, past A. Agresti and X.-50. Meng, Chapter i in Forcefulness in Numbers: The Rising of Academic Statistics Departments in the U.S., edited by A. Agresti and X.-Fifty. Meng, (2012) Springer. pdf file

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

Bayesian inference most odds ratio structure in ordinal contingency tables, (2013) (A. Agresti and M. Kateri), in special event of Environmetrics to honor the retentivity 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 result of invited contributions to the conference "Methods and Models on Latent Variables" held in Naples, Italian republic in May 2012. pdf file

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

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

Chiselled 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 outcome measures for interpreting models for ordinal categorical information, (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

The course 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).

Some bug in generalized linear modeling, in Springer proceedings of International Workshop on Matrices and Statistics, Funchal, Portugal (2020).

Interpreting effects in generalized linear modeling, (A. Agresti, C. Tarantola, and R. Varriale), Pages 1-8 in Statistical Learning and Modeling in Information Analysis}, edited by S. Balzano, G. Porzio, R. Salvatore, D. Vistocco, and Grand. Vichi, Springer (2021).

The foundations of statistical science: A history of textbook presentations, invited paper in Brazilian Journal of Probability and Statistics, with comments by several statisticians (including Sir David Cox, Bradley Efron, and Xiao-Li Meng), (2021). pdf file

Reflections on Murray Aitkin's contributions to nonparametric mixture models and Bayes factors, (Alan Agresti, Francesco Bartolucci, and Antonietta Mira), in special issue of Statistical Modelling to honour Murray Aitkin, (2022).

Unproblematic means to translate effects in modeling binary information, (A. Agresti, C. Tarantola, and R. Varriale), to announced in Trends and Challenges in Chiselled Information Assay, edited by Maria Kateri and Irini Moustaki, Springer, (2022).

A review of score-exam-based inference for categorical information, (A. Agresti, Southward. Giordano, and A. Gottard}, to appear in special event of Journal of Quantitative Economic science to honor C. R. Rao, (2022).

A few photos and links to seminars

Participants at workhop in my honor, "Categorical Data Analysis & Friends," Florence Italia, September 18, 2019.

Agresti pic8

"Grazie mille advertisement Anna Gottard per aver organizzato questo meraviglioso evento." And thanks to my Italian friends who came from Padova, Milano, Roma, Pavia, Firenze, Napoli, Venezia, Perugia, Parma, Bologna, Bergamo, Cosenza, Trento, and Verona. Hither is the program about the Florence workshop, and here is the talk I gave with reminiscences of visits to Italian universities. In 2021 I initiated and funded the "Premio a Giovani Studiosi e Studiose per Contributi alle Discipline Statistiche," an almanac honor for the outstanding Italian statistician nether age 40; Daniele Durante won the first honor.

My roots (and 2 of my favorite spots on earth)

Agresti pic3 Ferrazzano, Molise, Italy (la citta` di mia nonna italiana)

Agresti pic1 Wood of Dean, Gloucestershire, England (the land of my female parent and my British grandparents)

Here is a seminar (in mp4 format) on the History of Categorical Data Analysis that I presented in October 2015 at Istat (the Italian Demography Bureau) in Rome, Italy

Hither is a YouTube video of a seminar on Simple Ways to Translate Effects in Modeling Binary and Ordinal Information presented in 2021 for National University of Rosario, Argentine republic (and too at La Sapienza University in Rome and Ca' Foscari in Venice, Italy, and at Ohio State Academy)

Hither are Power Betoken slides from a seminar on Doubt (about Covid and related things, in Italian), presented at Padova, Italy in December 2020 by Antonietta Mira of the University of Insubria (Italia) and Academy of Lugano (Svizzera Italiana), with my help.

Jacki and Alan's Pound-wise guide to London from the December--Jan 2007 issue of Gainesville magazine. (My married woman Jacki Levine is founder and was editor of this bi-monthly magazine for 13 years.) More upwards-to-date, hither is a useful site, courtesy of Rick Steves, about experiencing untouristy London: Untouristy London. We would too advise Borough Market, and the walk forth the south banking concern of the Thames from the South Depository financial institution arts complex to the Tate and and so Tower Bridge (that role is touristy), but and then further east to Rotherhithe, stopping at the Mayflower pub.

The flick at the acme of my home page was taken past Jacki Levine in the Woods of Dean, Gloucestershire, UK, among the May bluebells.