Using SAS for data management, statistical analysis, and graphics / Ken Kleinman, Nicholas J. Horton.

Includes bibliographical references and index.

"A unique companion for statistical coders, Using SAS for Data Management, Statistical Analysis, and Graphics presents an easy way to learn how to perform an analytical task in SAS, without having to navigate through the extensive, idiosyncratic, and sometimes unwieldy software documentation. Organized by short, clear descriptive entries, the book covers many common tasks, such as data management, descriptive summaries, inferential procedures, regression analysis, multivariate methods, and the creation of graphics." "Through the extensive indexing, cross-referencing, and worked examples in this text, users can directly find and implement the material they need. The text includes convenient indices organized by topic and SAS syntax. Demonstrating the SAS code in action and facilitating exploration, the authors present example analyses that employ a single dataset from the HELP study. They also provide several case studies of more complex applications. Datasets and code are available for download on the book's Web site." "Features" "Presents worked examples that highlight the most useful portions of the extensive SAS language" "Covers various aspects of data management, from reading and exporting data to mathematical functions, logic, coding, and simulations" "Describes a wide variety of statistical tests and models, including linear regression and ANOVA, logistic and Poisson regression, models for clustered or correlated data, and more" "Shows how to control output using ODS" "Highlights the new graphics of SAS 9.2" "Helping to improve your analytical skills, this book lucidly summarizes the features of SAS most often used by statistical analysts. New users of SAS will find the simple approach easy to understand while more expert SAS programmers will appreciate the invaluable source of task-oriented information."--BOOK JACKET.

opc 09/05/13

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