R for SAS and SPSS Users
R is a powerful and free software system for data analysis and graphics, with over 4,000 add-on packages available. This book introduces R using SAS and SPSS terms with which you are already familiar. It demonstrates which of the add-on packages are most
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Robert A. Muenchen
R for SAS and SPSS Users
Second Edition
Robert A. Muenchen University of Tennessee Research Computing Support 109 Hoskins Library 1400 W. Cumberland Knoxville, TN 37996-4005 USA [email protected]
Series Editors: J. Chambers Department of Statistics Sequoia Hall 390 Serra Mall Stanford University Stanford, CA 94305-4065
D. Hand Department of Mathematics Imperial College London, South Kensington Campus London SW7 2AZ United Kingdom
W. Härdle C.A.S.E. Centre for Applied Statistics and Economics School of Business and Economics Humboldt-Universität zu Berlin Unter den Linden 6 10099 Berlin Germany
ISSN 1431-8784 ISBN 978-1-4614-0684-6 e-ISBN 978-1-4614-0685-3 DOI 10.1007/978-1-4614-0685-3 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011933470
© Springer Science+Business Media, LLC 2011 All rights reserved. This work may not be translated or copied in whole or in part without the written permission of the publisher (Springer Science+Business Media, LLC, 233 Spring Street, New York, NY 10013, USA), except for brief excerpts in connection with reviews or scholarly analysis. Use in connection with any form of information storage and retrieval, electronic adaptation, computer software, or by similar or dissimilar methodology now known or hereafter developed is forbidden. The use in this publication of trade names, trademarks, service marks, and similar terms, even if they are not identified as such, is not to be taken as an expression of opinion as to whether or not they are subject to proprietary rights. Printed on acid-free paper Springer is part of Springer Science+Business Media (www.springer.com)
Preface
While SAS and SPSS have many things in common, R is very different. My goal in writing this book is to help you translate what you know about SAS or SPSS into a working knowledge of R as quickly and easily as possible. I point out how they differ using terminology with which you are familiar, and show you which add-on packages will provide results most like those from SAS or SPSS. I provide many example programs done in SAS, SPSS, and R so that you can see how they compare topic by topic. When finished, you should know how to:
Install R, choose a user interface, and choose and install add-on packages. Read data from various sources such as text or Excel files, SAS or SPSS data sets, or relational databases. Manage your data through transformations, recodes, and combining data sets from both the add-cases and add-variables approaches and restructuring data from wide to long formats and vice versa. Create publication-quality graphs including bar, histogram, pie, line, scatter, regression, box, error bar, and interaction plots. Perform the basic types of analyses to measure strength of association and group differences, and be able to know where to turn to learn how to do more complex methods.
Who This Book Is For This book teaches R requiring no prior knowledge of statistical softw
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