An accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.
An accessible and practical guide to the use of applied regression models in testing and evaluating hypotheses dealing with social relationships, with example applications using relevant statistical methods in both Stata and R.Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
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.
Inhaltsangabe
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.
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.
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