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English
Cambridge University Press
17 August 2023
This accessible and practical textbook gives students the perfect guide to the use of regression models in testing and evaluating hypotheses dealing with social relationships. A range of statistical methods suited to a wide variety of dependent variables is explained, which will allow students to read, understand, and interpret complex statistical analyses of social data. Each chapter contains example applications using relevant statistical methods in both Stata and R, giving students direct experience of applying their knowledge. A full suite of online resources - including statistical command files, datasets and results files, homework assignments, class discussion topics, PowerPoint slides, and exam questions - supports the student to work independently with the data, and the instructor to deliver the most effective possible course. This is the ideal textbook for advanced undergraduate and beginning graduate students taking courses in applied social statistics.

By:   , , ,
Imprint:   Cambridge University Press
Country of Publication:   United Kingdom
Dimensions:   Height: 253mm,  Width: 177mm,  Spine: 25mm
Weight:   1.140kg
ISBN:   9781108926263
ISBN 10:   1108926266
Pages:   400
Publication Date:  
Audience:   College/higher education ,  A / AS level
Format:   Paperback
Publisher's Status:   Active
List of figures; List of tables; Preface; 1. Introduction; 2. Undertaking statistical analysis using Stata; 3. Undertaking statistical analysis using R; 4. Descriptive statistics and the normal distribution; 5. Statistical tables and cross-tabulations; 6. Bivariate regression and correlation and statistical inference; 7. Multiple regression and correlation; 8. Regression assumptions and diagnostics and robust regression; 9. Missing data; 10. Issues of survey design; 11. Binomial logistic regression; 12. Ordinal logistic regression; 13. Multinomial logistic regression; 14. Count regression; 15. Survival analysis; 16. Multilevel models; 17. Other issues and final; References; Index.

Dudley L. Poston, Jr., is Emeritus Professor of Sociology at Texas A&M University. He held adjunct professor positions at People's (Renmin) University of China, Fuzhou University, and Nanjing Normal University. He has published twenty-two books and over 380 journal articles, book chapters, and related reports, and has taught demography and statistics classes to around 1,000 graduate and 5,000 undergraduate students. Eugenia Conde is a statistical consultant at the H. W. Odum Institute for Research in Social Science at the University of North Carolina at Chapel Hill. She provides consultations to students and faculty on research methods and statistics. Layton M. Field is an associate professor at Mount St. Mary's University, and Director of the Mount Community Advancement Resources in Training, Assessment, and Service program. He specializes in research methods and statistics, and has published articles in the areas of demography, sociology, and criminal justice.

Reviews for Applied Regression Models in the Social Sciences

'This textbook on applied regression by Poston, Conde, and Field is well suited for teaching graduate students in all of the social science fields, but is especially suited for demography, population studies, and public health. It is an excellent contribution to the teaching and practice of regression analysis in the twenty-first century that also can serve as a useful reference book for practitioners.' David Swanson, University of California, Riverside 'This textbook successfully combines theoretical statistical concepts and empirical research examples of applied regression models, from the basic to advanced ones. The best part is the detailed interpretations of the results of statistical analyses. Readers can truly understand the meanings and usages of these statistical numbers.' Lang-Wen Huang, Soochow University, Taipei 'Applied Regression Models in the Social Sciences excels in its focus on the application and interpretation of various regression models and its inclusion of commands in Stata and R. Its sequencing and topical coverage set it apart from others in that the reader is guided through the entire research process with a multitude of examples. This will be a valuable resource to faculty, students, and applied researchers alike.' Ginny Garcia-Alexander, University of Texas at San Antonio 'This textbook fills a critical void in the market for statistical tutorials by bridging the gap between elementary and advanced statistics and providing real-world examples in both Stata and R, allowing students to develop proficiency in the statistical software environments in highest demand. It strikes the perfect balance, neither oversimplifying nor overwhelming with complex mathematics, making it the ideal companion for graduate students seeking a solid foundation in the skills needed to generate social science findings with advanced insights. From correlation analysis to multi-level modeling, this comprehensive and versatile book covers a wide range of regression techniques, equipping learners with a diverse toolkit for trustworthy data analysis and allowing them to transition from the classroom to the laboratory with confidence. The authors' expertise shines through in this clear, comprehensive, and engaging book that is destined to be an indispensable resource.' Stephanie Bohon, University of Tennessee


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