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Levine's guide to SPSS for analysis of variance PDF

210 Pages·2005·8.67 MB·English
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GetPedia Levine’s Guide to SPSS for Analysis of Variance 2nd Edition Levine’s Guide to SPSS for Analysis of Variance 2nd Edition Melanie C. Page Oklahoma State University Sanford L. Braver Arizona State University David P. MacKinnon Arizona State University LAWRENCE ERLBAUM ASSOCIATES, PUBLISHERS 2003 Mahwah, New Jersey London Copyright © 2003 by Lawrence Erlbaum Associates, In.c All rights reserved. No part of the book may be reproduced in any form, by photostat, microform, retrieval system, or any other means, without the prior written permission of the publisher. Lawrence Erlbaum Associates, Inc., Publishers 10 Industrial Avenue Mahwah, New Jersey 07430 Cover design by Kathryn Houghtaling Lacey Library of Congress Cataloging-in-Publication Data Page, Melanie C.– Levine’s guide to SPSS for analysis of variance / Melanie C. Page, Sanford L. Braver, David P. Mackinnon. — 2nd ed. p. cm. Rev. ed. of: A guide to SPSS for analysis of variance. 1991. Includes bibliographical references and index. ISBN 0-8058-3095-2 (cloth : alk. paper) — ISBN 0-8058-3096-0 (pbk. : alk. paper) 1. SPSS (Computer file) 2. Analysis of variance—Computer programs. I. Page, Melanie C. II. Braver, Sanford L. III. Mackinnon, David Peter, 1957– IV. Title. HA31.35.L48 2003 519.5′0285′5369—dc21 2003040883 CIP In addition to the sources cited in the text for the data set used, several additional data sets are included on the CD-Rom and are from the following sources: From The analysis of covariance and alternatives. (p. 225), by B. E. Huitema, 1980, New York, John Wiley & Sons. Copyright 1980 by John Wiley & Sons, Inc. This material is used by permission of John Wiley & Sons, Inc. From Design and Analysis: A Researcher’s Handbook (p. 161), by G. Keppel, 1991, Upper Saddle River, NJ, Pearson Education. Copyright 1991 by Pearson Education, Inc. Reprinted with permission. J. P. Stevens (1999). Intermediate statistics: A modern approach (2nd ed.), p. 174. Copyright by Lawrence Erlbaum Associates. Reprinted with permission. J. P. Stevens (1999). Intermediate statistics: A modern approach (2nd ed.), p. 358. Copyright by Lawrence Erlbaum Associates. Reprinted with permission. From Computer-assisted research deign and analysis (p. 417), B. G. Tabachnick & L. S. Fidell, 2001, Needham Heights, MA, Allyn & Bacon. Copyright 2001 by Pearson Education, Inc. Reprinted/adapted by permission of the publisher. From Statistical principles in experimental design (3rd ed.) (p. 853), B. J. Winer, D. R. Brown, & K. M. Michels, 1991, New York, McGraw- Hill. Copyright 1991 by The McGraw Hill Companies, Inc. Books published by Lawrence Erlbaum Associates are printed on acid-free paper, and their bindings are chosen for strength and durability. Printed in the United States of America 10 9 8 7 6 5 4 3 2 1 Contents PREFACE ix Table of Topics xi 1 USING SPSS AND USING THIS BOOK 1 Conventions for Syntax Programs 1 Creating Syntax Programs in Windows 2 2 READING IN AND TRANSFORMING VARIABLES FOR ANALYSIS IN SPSS 5 Reading In Data With Syntax 5 Entering Data with the “DATA LIST” Command 6 “FREE” or “FIXED” Data Format 7 Syntax for Using External Data 9 Data Entry for SPSS for Windows Users 9 Importing Data 11 Saving and Printing Files 12 Opening Previously Created and Saved Files 12 Output Examination 12 Data Transformations and Case Selection 14 “COMPUTE” 14 “IF” 15 “RECODE” 15 “SELECT IF” 15 Data Transformations with PAC 16 3 ONE-FACTOR BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 20 Basic Analysis of Variance Commands 20 Testing the Homogeneity of Variance Assumption 24 Comparisons 24 Planned Contrasts 25 Post Hoc Tests 28 Trend Analysis 32 Monotonic Hypotheses 36 PAC 37 v vi CONTENTS 4 TWO-FACTOR BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 42 Basic Analysis of Variance Commands 42 The Interaction 45 Unequal N Factorial Designs 45 Planned Contrasts and Post Hoc Analyses of Main Effects 49 Exploring a Significant Interaction 51 Simple Effects 51 Simple Comparisons and Simple Post Hocs 52 Interaction Contrasts 53 Trend Interaction Contrasts and Simple Trend Analysis 55 PAC 56 5 THREE (AND GREATER) FACTOR BETWEEN-SUBJECTS ANALYSIS OF VARIANCE 59 Basic Analysis of Variance Commands 59 Exploring a Significant Three-Way Interaction 62 Simple Two-Way Interactions 62 A Nonsignificant Three-Way: Simple Effects 63 Interaction Contrasts, Simple Comparisons, Simple Simple Comparisons, and Simple Interaction Contrasts 64 Collapsing (Ignoring) a Factor 66 More Than Three Factors 66 PAC 66 6 ONE-FACTOR WITHIN-SUBJECTS ANALYSIS OF VARIANCE 67 Basic Analysis of Variance Commands 67 Analysis of Variance Summary Tables 70 Correction for Bias in Tests of Within-Subjects Factors 70 Planned Contrasts 72 The “TRANSFORM/RENAME” Method for Nonorthogonal Contrasts 73 The “CONTRAST/WSDESIGN” Method for Orthogonal Contrasts 74 Post Hoc Tests 75 PAC 75 7 TWO- (OR MORE) FACTOR WITHIN-SUBJECTS ANALYSIS OF VARIANCE 81 Basic Analysis of Variance Commands 81 Analysis of Variance Summary Tables 84 Main Effect Contrasts 84 Analyzing Orthogonal Main Effects Contrasts (Including Trend Analysis) Using “CONTRAST/WSDESIGN” 85 Nonorthogonal Main Effects Contrasts Using “TRANSFORM/RENAME” 86 Simple Effects 88 Analyzing Orthogonal Simple Comparisons Using “CONTRAST/WSDESIGN” 89 Analyzing Orthogonal Interaction Contrasts Using “CONTRAST/WSDESIGN” 90 Nonorthogonal Simple Comparisons Using “TRANSFORM/RENAME” 90 Nonorthogonal Interaction Contrasts Using “TRANSFORM/RENAME” 92 Post Hocs 92 More Than Two Factors 92 PAC 93 CONTENTS vii 8 TWO-FACTOR MIXED DESIGNS IN ANALYSIS OF VARIANCE: ONE BETWEEN-SUBJECTS FACTOR AND ONE WITHIN-SUBJECTS FACTOR 97 Basis Analysis of Variance Commands 97 Main Effect Contrasts 100 Between-Subjects Factor(s) 100 Within-Subjects Factor(s) 100 Interaction Contrasts 104 Simple Effects 104 Simple Comparisons 107 Post Hocs and Trend Analysis 109 PAC 109 9 THREE- (OR GREATER) FACTOR MIXED DESIGNS 111 Simple Two-Way Interactions 112 Simple Simple Effects 113 Main Effect Contrasts and Interaction Contrasts 114 Simple Contrasts: Simple Comparisons, Simple Simple Comparisons, and Simple Interaction Contrasts 116 PAC 119 10 ANALYSIS OF COVARIANCE 120 Testing the Homogeneity of Regression Assumption 122 Multiple Covariates 123 Contrasts 124 Post Hocs 124 Multiple Between-Subjects Factors 124 ANCOVAs in Designs With Within-Subjects Factors 125 Constant Covariate 125 Varying Covariate 127 PAC 131 11 DESIGNS WITH RANDOM FACTORS 132 Random Factors Nested in Fixed Factors 133 Subjects as Random Factors in Within-Subjects Designs: The One-Line-per-Level Setup 134 The One-Factor Within-Subjects Design 134 Two-Factor Mixed Design 138 Using One-Line-per-Level Setup to Get Values to Manually Compute Adjusted Means in Varying Covariate Within-Subjects ANCOVA 140 PAC 143 12 MULTIVARIATE ANALYSIS OF VARIANCE: DESIGNS WITH MULTIPLE DEPENDENT VARIABLES TESTED SIMULTANEOUSLY 145 Basic Analysis of Variance Commands 145 Multivariate Planned Contrasts and Post Hocs 149 Extension to Factorial Between-Subjects Designs 150 Multiple Dependent Variables in Within-Subject Designs: Doubly Multivariate Designs 150 Contrasts in Doubly Multivariate Designs 153 PAC 157 viii CONTENTS 13 GLM AND UNIANOVA SYNTAX 166 One-Factor Between-Subjects ANOVA 166 Basic Commands 166 Contrasts 168 Post Hoc Tests 171 Two-Factor Between-Subjects ANOVA 171 Unequal N 171 Main Effects Contrasts and Post Hocs 171 Simple Effects 174 Simple Comparisons 176 Interaction Contrasts 176 Three or More Factor ANOVA 177 One-Factor Within-Subjects ANOVA 177 Basic Commands 177 Planned Contrasts 178 Post Hoc Tests 179 Two or More Factor Within-Subjects ANOVA 179 Main Effect and Interaction Contrasts 180 Simple Effects and Simple Comparisons 181 Mixed Designs 183 More Complex Analyses 183 REFERENCES 185 APPENDIX A 186 APPENDIX B 188 Author Index 189 Subject Index 191

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