Data Analysis Using Stata provides a comprehensive introduction to Stata with an emphasis on data management, linear regression, logistic modeling, and using programs to automate repetitive tasks. Throughout the book, the authors make extensive use of examples using data from the German Socioeconomic Panel, a large survey of households containing demographic, income, employment, and other key information.
The book begins with an introduction to the Stata interface and then proceeds with a discussion of Stata syntax and simple programming tools like foreach loops. The core of the book includes chapters on producing tables and graphs, performing linear regression, and using logistic regression. The remainder of the book includes chapters on reading text files, writing programs and ado-files, and Internet resources, such as the search command and the SSC archive. All key concepts are illustrated with multiple examples.
Data Analysis Using Stata will serve as a valuable introduction to Stata, both for those who are new to statistics and statistical computing as well as for those new to Stata but familiar with other programs.
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Social Science Research Center, Berlin University of Maryland, College Park, Maryland, USA
[The authors] transform the book into an interactive experience, making it both more enjoyable and more effective as a learning tool. A unique and highly valuable feature of the book is its holistic approach to dataset construction and analysis and the strategies it provides for organizing the entire process so that it can be easily reproduced and, when necessary, modified. ...The potential payoff includes not only avoiding wasted time spent trying to figure out what you did weeks, months, or even years ago, but more importantly, the ability to work more efficiently with less chance of error. Perhaps the most important strength of the book is the impression of data analysis it conveys, namely, as an activity involving careful thought, a lot of time spent looking at data in tabular or graphical form, and a careful assessment of the adequacy of any model fit to the data. In this respect, the book could serve as a helpful corrective for students in disciplines where the methods courses are overly focused on statistical tests and the mechanical application of 'accepted' models.
- L. Philip Schumm, The Stata Journal, 2005
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