No previous knowledge of statistics is assumed, and mathematical background is assumed to be minimal lowest-level high-school algebra. The book contains sufficient material for a two-semester sequence of courses. Such sequences are commonly required of social science graduate students in sociology, political science, and psychology. Students in geography, anthropology, journalism, and speech also are sometimes required to take at least one statistics course. From reader reviews: William McClanahan: Exactly why? Because this Statistical Methods for the Social Sciences 4th Edition is an unordinary book that the inside of the book waiting for you to snap this but latter it will distress you with the secret the item inside.
|Published (Last):||14 October 2011|
|PDF File Size:||18.88 Mb|
|ePub File Size:||10.96 Mb|
|Price:||Free* [*Free Regsitration Required]|
This new edition shows how to do all analyses using R software and add some new material e. This book, 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.
For some data files from the text, click on data files for Intro CDA, 3rd edition. For some data files from the 2nd edition, click on data files 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.
The text Foundations of Linear and Generalized Linear Models , published by Wiley in February , presents an overview of the most commonly used statistical models by 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 data 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 data. The book also introduces quasi-likelihood methods such as generalized estimating equations , linear mixed models and generalized linear mixed models with random effects for clustered correlated data, Bayesian linear and generalized linear modeling, and regularization methods for high-dimensional data.
The book has more than exercises. Here is an interview about the book in the Wiley publication "Statistics Views. This book has a chapter for each of about 40 Statistics and Biostatistics departments founded in the U. Included are about historical photos. See the Springer site for other details.
Here is an interview that the Wiley publication "Statistics Views" conducted with me to mark the publication of the new edition.
A website for second edition has some material for the 2nd edition. Laura Thompson has prepared a detailed manual on the use of R or S-Plus to conduct all the analyses in the 2nd edition. The text Analysis of Ordinal Categorical Data Wiley, has been revised, and the second edition was published in The latest 4th edition was co-authored by Bernhard Klingenberg of Williams College, who has developed a wonderful set of applets and other resources for teaching from the book see Art of Stat.
This text is designed for a one-term or two-term undergraduate course or a high school AP course on an introduction to statistics, presented with a conceptual approach. Contact Ms. Agresti and B. Finlay, published 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 as well as 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, go to applets. See R data files. He has also put the data files at a GitHub site, data files at GitHub. For examples of the use of the software Stata for various analyses for examples in the 4th edition of this text, see the useful site set up by the UCLA Statistical Computing Center. 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 degradation of the springs in north-central Florida see www.
I am also pleased to report due to my partial Italian heritage that there is also 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 e Avanzati per le scienze sociali published by Pearson, and there is also a Portuguese version -- see "Metodos Estatisticos para as Ciencas Socias" at Portuguese SMSS -- and a Chinese version, and it is being translated into Spanish.
I have developed Powerpoint files for lectures from Chapters of this text that are available to instructors using this text. Please contact me for details. Finally, here is a link to a workshop held by the Department of Sociology, Oxford University, in that discussed issues in the teaching of quantitative methods to social science students.
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. 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. Analysis of Ordinal Categorical Data, 2nd ed.
An Introduction to Categorical Data Analysis, 3rd ed. Categorical Data Analysis, 3rd edition, Wiley Some Articles Bounds on the extinction time distribution of a branching process. Advances in Applied Probability, 6 , Journal of Applied Probability, 12 , Journal of the American Statistical Association, 71 , Some exact conditional tests of independence for r x c cross-classification tables. Wackerly Psychometrika, 42 , Journal of the American Statistical Association, 72 , A coefficient of multiple association based on ranks.
Communications in Statistics, A6 , Statistical analysis of qualitative variation. Agresti , Chapter 10, in Sociological Methodology ed.
Schuessler, Jossey-Bass Publ. Descriptive measures for rank comparisons of groups. Exact conditional tests for cross-classifications: Approximation of attained significance level. Wackerly and J. Boyett , Psychometrika, 44 , Schollenberger, A. Agresti, and D. Generalized odds ratios for ordinal data. Biometrics, 36 , Journal of the Royal Statistical Society B, 43 , Measures of nominal-ordinal association, Journal of the American Statistical Association, 76 , Encyclopedia of the Statistical Sciences, Vol.
Testing marginal homogeneity for ordinal categorical variables, Biometrics, 39, , Association models for multidimensional cross-classifications of ordinal variables with A. Kezouh , invited paper for issue on categorical data, Communications in Statistics, A12 , A simple diagonals-parameter symmetry and quasisymmetry model, Statistics and Probability Letters, 1 , Morey , Educational and Psychological Measurement, 44 , Ordinal data. Comparing mean ranks for repeated measures data with J.
Pendergast , Communications in Statistics, A15 , Chuang , Statistics in Medicine, 5 , Applying R-squared type measures to ordered categorical data, Technometrics, 28 , Schollenberger and D. Chuang and A. Kezouh , Journal of the American Statistical Association, 82 , Bayesian and maximum likelihood approaches to order-restricted inference for models for ordinal categorical data with C.
Chuang , pp. Dykstra, T. Robertson, and F. Wright, New York: Springer-Verlag. An empirical investigation of some effects of sparseness in contingency tables with M. A model for agreement between ratings on an ordinal scale, Biometrics, 44 , Logit models for repeated ordered categorical response data, invited paper for Proceedings of 13th SAS Users Group Conference, , An agreement model with Kappa as parameter, Statistics and Probability Letters, 7 , Model-based Bayesian methods for estimating cell proportions in cross-classification tables having ordered categories with C.
A tutorial on modeling ordered categorical response data, Psychological Bulletin, , A survey of models for repeated ordered categorical response data, Statistics in Medicine, 8 , Exact inference for contingency tables with ordered categories with C.
Mehta and N. Patel , Journal of the American Statistical Association, 85 , Analysis of sparse repeated categorical measurement data with S. Lipsitz and J. Parsimonious latent class models for ordinal variables, invited paper in Proceedings of 6th International Workshop on Statistical Modeling, , , Utrecht, Netherlands.
Becker and A. Agresti , Statistics in Medicine, 11 , Comparing marginal distributions of large, sparse contingency tables with S. Lang , Computational Statistics and Data Analysis, 14 ,
Statistical Methods for the Social Sciences (4th Edition) by Alan Agresti, Barbara Finlay
Statistical Methods for the Social Sciences, 4th Edition