Behavioral Research Data Analysis with R
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. The authors aim primarily to help practitioners of behavioral research make the
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For further volumes: http://www.springer.com/series/6991
Use R! Albert: Bayesian Computation with R Bivand/Pebesma/G´omez-Rubio: Applied Spatial Data Analysis with R Cook/Swayne: Interactive and Dynamic Graphics for Data Analysis: With R and GGobi Hahne/Huber/Gentleman/Falcon: Bioconductor Case Studies Paradis: Analysis of Phylogenetics and Evolution with R Pfaff: Analysis of Integrated and Cointegrated Time Series with R Sarkar: Lattice: Multivariate Data Visualization with R Spector: Data Manipulation with R
Yuelin Li • Jonathan Baron
Behavioral Research Data Analysis with R
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Yuelin Li Memorial Sloan-Kettering Cancer Center Department of Psychiatry and Behavioral Sciences 641 Lexington Ave. 7th Floor New York, New York 10022-4503 USA [email protected]
Jonathan Baron Department of Psychology University of Pennsylvania 3720 Walnut Street Philadelphia, Pennsylvania 19104-6241 USA [email protected]
Series Editors: Robert Gentleman Program in Computational Biology Division of Public Health Sciences Fred Hutchinson Cancer Research Center 1100 Fairview Ave. N, M2-B876 Seattle, Washington 98109-1024 USA
Kurt Hornik Department f¨ur Statistik und Mathematik Wirtschaftsuniversit¨at Wien Augasse 2-6 A-1090 Wien Austria
Giovanni Parmigiani The Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins University 550 North Broadway Baltimore, MD 21205-2011 USA
ISBN 978-1-4614-1237-3 e-ISBN 978-1-4614-1238-0 DOI 10.1007/978-1-4614-1238-0 Springer New York Dordrecht Heidelberg London Library of Congress Control Number: 2011940221 © Springer Science+Business Media, LLC 2012 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
This book is written for behavioral scientists who want to consider adding R to their existing set of statistical tools, or want to switch to R as their main computation tool. We aim primarily to help practioners of behavioral research make the transition to R. The focus is to provide practical advice on some of the widely used statistical methods in behavioral research, using a set of notes and annotated examples. We also aim to help beginners learn more about statistics and behavioral research. These are statistical techniques used by psychologists who do research on human subjects, but of course they are also relevant
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