Titolo: A Handbook of Statistical Analyses Using Stata, 4th Edition
Autori: Rabe-Hesketh Sophia, Everitt Brian S.
Autori: Rabe-Hesketh Sophia, Everitt Brian S.
Publisher: Chapman & Hall/CRC
Copyright: 2007
ISBN-10: 1-58488-756-7
ISBN-13: 978-1-58488-756-0
Pages: 352; paperback
Price: $58.00
Supplements: datasets
A Handbook of Statistical Analyses Using Stata, Fourth Edition: Sophia Rabe-Hesketh, Brian S. Everitt
Fourth Edition Book Description
Fully updated, the fourth edition of this highly acclaimed and perpetually bestselling text demonstrates how a wide variety of statistical analyses, including descriptive statistics, graphics, and model estimation and diagnostics, can be performed using Stata version 9. The authors present many of Stata's novel features, including a new mixed-models estimation command and a new matrix language. This edition also contains additional exercises that use various data sets and numerous examples of real-life data, enabling a better understanding of the methodology. The book offers selected solutions in an appendix as well as a solutions manual with qualifying course adoptions.
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Comment from the Stata technical group
The fourth edition of A Handbook of Statistical Analyses Using Stata, by Sophia Rabe-Hesketh and Brian Everitt, is now available and incorporates many of the features introduced in Stata 9. The book provides practical examples of using Stata for real-world analysis. It begins with a concise 41-page introduction to Stata and progresses to intermediate topics such as multiple regression, ANOVA, and logistic regression. Chapter-length discussions cover more advanced topics, such as the generalized linear model (GLM), survival analysis, maximum likelihood estimation, cluster analysis, and principal components analysis.
The most distinguishing feature of this text is its use of case studies to help users learn Stata’s capabilities in the various subfields of statistics, including generalized linear models, survival analysis, panel (longitudinal) data, and cluster analysis. For example, the discussion of survival analysis revolves around a study of methadone maintenance treatment to aid heroin addicts in overcoming their addiction.
A Handbook of Statistical Analysis Using Stata would make an excellent supplemental textbook in a course in statistics, allowing students to learn Stata on their own while reviewing concepts taught during lectures. The book will also help practitioners, particularly those in biostatistics and the health sciences, to become proficient with Stata quickly
Supplements: datasets
A Handbook of Statistical Analyses Using Stata, Fourth Edition: Sophia Rabe-Hesketh, Brian S. Everitt
Fourth Edition Book Description
Fully updated, the fourth edition of this highly acclaimed and perpetually bestselling text demonstrates how a wide variety of statistical analyses, including descriptive statistics, graphics, and model estimation and diagnostics, can be performed using Stata version 9. The authors present many of Stata's novel features, including a new mixed-models estimation command and a new matrix language. This edition also contains additional exercises that use various data sets and numerous examples of real-life data, enabling a better understanding of the methodology. The book offers selected solutions in an appendix as well as a solutions manual with qualifying course adoptions.
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pdf@Rapidshare.com
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http://www.psypress.com/handbook-of-statistical-analyses-using-stata-fourth-edition-9781584887560
Comment from the Stata technical group
The fourth edition of A Handbook of Statistical Analyses Using Stata, by Sophia Rabe-Hesketh and Brian Everitt, is now available and incorporates many of the features introduced in Stata 9. The book provides practical examples of using Stata for real-world analysis. It begins with a concise 41-page introduction to Stata and progresses to intermediate topics such as multiple regression, ANOVA, and logistic regression. Chapter-length discussions cover more advanced topics, such as the generalized linear model (GLM), survival analysis, maximum likelihood estimation, cluster analysis, and principal components analysis.
The most distinguishing feature of this text is its use of case studies to help users learn Stata’s capabilities in the various subfields of statistics, including generalized linear models, survival analysis, panel (longitudinal) data, and cluster analysis. For example, the discussion of survival analysis revolves around a study of methadone maintenance treatment to aid heroin addicts in overcoming their addiction.
A Handbook of Statistical Analysis Using Stata would make an excellent supplemental textbook in a course in statistics, allowing students to learn Stata on their own while reviewing concepts taught during lectures. The book will also help practitioners, particularly those in biostatistics and the health sciences, to become proficient with Stata quickly
