Using R With Multivariate Statistics PDF
Preview Using R With Multivariate Statistics
Using R With Multivariate Statistics 2 To Joanne For all her love and support while writing the book. 3 Using R With Multivariate Statistics Randall E. Schumacker University of Alabama 4 FOR INFORMATION: SAGE Publications, Inc. 2455 Teller Road Thousand Oaks, California 91320 E-mail: [email protected] SAGE Publications Ltd. 1 Oliver’s Yard 55 City Road London EC1Y 1SP United Kingdom SAGE Publications India Pvt. Ltd. B 1/I 1 Mohan Cooperative Industrial Area Mathura Road, New Delhi 110 044 India SAGE Publications Asia-Pacific Pte. Ltd. 3 Church Street #10-04 Samsung Hub Singapore 049483 Copyright © 2016 by SAGE Publications, Inc. All rights reserved. No part of this book may be reproduced or utilized in any form or by any means, electronic or mechanical, including photocopying, recording, or by any information storage and retrieval system, without permission in writing from the publisher. All trademarks depicted within this book, including trademarks appearing as part of a screenshot, figure, or other image are included solely for the purpose of illustration and are the property of their respective holders. The use of the trademarks in no way indicates any relationship with, or endorsement by, the holders of said trademarks. SPSS is a registered trademark of International Business Machines Corporation. Printed in the United States of America Library of Congress Cataloging-in-Publication Data Schumacker, Randall E. Using R with multivariate statistics : a primer / Randall E. Schumacker, University of Alabama, Tuscaloosa. pages cm Includes bibliographical references and index. ISBN 978-1-4833-7796-4 (pbk. : alk. paper) 1. Multivariate analysis—Data processing. 2. R (Computer program language) 3. Statistics—Data processing. I. Title. QA278.S37 2016 519.5’3502855133—dc23 2015011814 This book is printed on acid-free paper. 5 Acquisitions Editor: Vicki Knight Editorial Assistant: Yvonne McDuffee eLearning Editor: Katie Bierach Production Editor: Kelly DeRosa Copy Editor: QuADS Prepress (P) Ltd. Typesetter: C&M Digitals (P) Ltd. Proofreader: Jennifer Grubba Indexer: Michael Ferreira Cover Designer: Michelle Kenny Marketing Manager: Nicole Elliott 6 Detailed Contents 7 8 Detailed Contents Preface Acknowledgments About the Author 1. Introduction and Overview Background Persons of Interest Factors Affecting Statistics R Software Web Resources References 2. Multivariate Statistics: Issues and Assumptions Issues Assumptions Normality Determinant of a Matrix Equality of Variance–Covariance Matrix Box M Test SPSS Check Summary Web Resources References 3. Hotelling’s T2: A Two-Group Multivariate Analysis Overview Assumptions Univariate Versus Multivariate Hypothesis Statistical Significance Practical Examples Using R Single Sample Two Independent Group Mean Difference Two Groups (Paired) Dependent Variable Mean Difference Power and Effect Size A Priori Power Estimation Effect Size Measures Reporting and Interpreting Summary Exercises Web Resources 9 References 4. Multivariate Analysis of Variance MANOVA Assumptions Independent Observations Normality Equal Variance–Covariance Matrices Summary MANOVA Example: One-Way Design MANOVA Example: Factorial Design Effect Size Reporting and Interpreting Summary Exercises Web Resources References 5. Multivariate Analysis of Covariance Assumptions Multivariate Analysis of Covariance MANCOVA Example Dependent Variable: Adjusted Means Reporting and Interpreting Propensity Score Matching Summary Web Resources References 6. Multivariate Repeated Measures Assumptions Advantages of Repeated Measure Design Multivariate Repeated Measure Examples Single Dependent Variable Several Dependent Variables: Profile Analysis Doubly Multivariate Repeated Measures Reporting and Interpreting Results Summary Exercises Web Resources References 7. Discriminant Analysis Overview Assumptions 10
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