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SPSS Amos 7.0 User's Guide PDF

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Amos™ 7.0 User’s Guide James L. Arbuckle For more information, please contact: Marketing Department Amos Development Corporation SPSS, Inc. 1121 N. Bethlehem Pike, Suite 60 - #142 233 S. Wacker Dr., 11th Floor Spring House, PA 19477, U.S.A. Chicago, IL 60606-6307, U.S.A. URL: http://amosdevelopment.com Tel: (312) 651-3000 Fax: (312) 651-3668 URL: http://www.spss.com SPSS® is a registered trademark and the other product names are the trademarks of SPSS Inc. for its proprietary computer software. Amos™ is a trademark of Amos Development Corporation. No material describing such software may be produced or distributed without the written permission of the owners of the trademark and license rights in the software and the copyrights in the published materials. The SOFTWARE and documentation are provided with RESTRICTED RIGHTS. Use, duplication, or disclosure by the Government is subject to restrictions as set forth in subdivision (c)(1)(ii) of the Rights in Technical Data and Computer Software clause at 52.227-7013. Contractor/manufacturer is SPSS Inc., 233 S. Wacker Dr., 11th Floor, Chicago, IL 60606-6307. Access®, Excel®, Explorer®, FoxPro®, Microsoft®, Visual Basic®, and Windows® are registered trademarks of Microsoft Corporation. General notice: Other product names mentioned herein are used for identification purposes only and may be trademarks of their respective companies. Microsoft® Visual Basic® and Windows® screen shots reproduced by permission of Microsoft Corporation. Amos 7.0 User’s Guide Copyright © 1995–2006 by Amos Development Corporation All rights reserved. Printed in the United States of America. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the publisher. 1 2 3 4 5 6 7 8 9 0 09 08 07 06 ISBN-13: 978-1-56827-386-0 ISBN-10: 1-56827-386-X C o n t e n t s Part I: Getting Started 1 Introduction 1 Featured Methods. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2 About the Tutorial. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 About the Examples. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3 About the Documentation . . . . . . . . . . . . . . . . . . . . . . . . . . . 4 Other Sources of Information . . . . . . . . . . . . . . . . . . . . . . . . . 4 Acknowledgments . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5 2 New Features 7 Estimation for Ordered-Categorical and Censored Data. . . . . . . . . . 7 Data Imputation for Ordered-Categorical and Censored Data . . . . . . 8 No Bayesian Prerequisites. . . . . . . . . . . . . . . . . . . . . . . . . . . 9 3 Tutorial: Getting Started with Amos Graphics 11 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .11 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .12 Launching Amos Graphics. . . . . . . . . . . . . . . . . . . . . . . . . . .13 Creating a New Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . .14 iii Specifying the Data File . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15 Specifying the Model and Drawing Variables . . . . . . . . . . . . . . . 15 Naming the Variables . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16 Drawing Arrows . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17 Constraining a Parameter. . . . . . . . . . . . . . . . . . . . . . . . . . . 18 Altering the Appearance of a Path Diagram . . . . . . . . . . . . . . . . 19 Setting Up Optional Output . . . . . . . . . . . . . . . . . . . . . . . . . . 20 Performing the Analysis. . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Viewing Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 22 Printing the Path Diagram. . . . . . . . . . . . . . . . . . . . . . . . . . . 24 Copying the Path Diagram . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Copying Text Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 25 Part II: Examples 1 Estimating Variances and Covariances 27 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 27 Bringing In the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 28 Analyzing the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 29 Viewing Graphics Output . . . . . . . . . . . . . . . . . . . . . . . . . . . 32 Viewing Text Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 33 Optional Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 37 Distribution Assumptions for Amos Models . . . . . . . . . . . . . . . . 39 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 40 Modeling in C# . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 43 Other Program Development Tools . . . . . . . . . . . . . . . . . . . . . 44 iv 2 Testing Hypotheses 45 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .45 Parameters Constraints . . . . . . . . . . . . . . . . . . . . . . . . . . . .45 Moving and Formatting Objects. . . . . . . . . . . . . . . . . . . . . . . .49 Data Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .50 Optional Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .52 Labeling Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .55 Hypothesis Testing . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .56 Displaying Chi-Square Statistics on the Path Diagram. . . . . . . . . . .57 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .59 3 More Hypothesis Testing 63 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63 Bringing In the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .63 Testing a Hypothesis That Two Variables Are Uncorrelated . . . . . . .64 Specifying the Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .64 Viewing Text Output . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .66 Viewing Graphics Output. . . . . . . . . . . . . . . . . . . . . . . . . . . .67 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .69 4 Conventional Linear Regression 71 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .71 Analysis of the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .72 v Specifying the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 73 Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Fixing Regression Weights . . . . . . . . . . . . . . . . . . . . . . . . . . 74 Viewing the Text Output. . . . . . . . . . . . . . . . . . . . . . . . . . . . 76 Viewing Graphics Output . . . . . . . . . . . . . . . . . . . . . . . . . . . 78 Viewing Additional Text Output. . . . . . . . . . . . . . . . . . . . . . . . 79 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 81 5 Unobserved Variables 85 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85 Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Measurement Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 87 Structural Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 88 Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Specifying the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 89 Results for Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 94 Model B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 97 Results for Model B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 98 Testing Model B against Model A . . . . . . . . . . . . . . . . . . . . . 100 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 102 6 Exploratory Analysis 105 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 105 Model A for the Wheaton Data. . . . . . . . . . . . . . . . . . . . . . . 106 Model B for the Wheaton Data. . . . . . . . . . . . . . . . . . . . . . . 111 Model C for the Wheaton Data. . . . . . . . . . . . . . . . . . . . . . . 118 vi Multiple Models in a Single Analysis. . . . . . . . . . . . . . . . . . . . 120 Output from Multiple Models . . . . . . . . . . . . . . . . . . . . . . . . 123 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 127 7 A Nonrecursive Model 133 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 133 Felson and Bohrnstedt’s Model . . . . . . . . . . . . . . . . . . . . . . . 134 Model Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Results of the Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 135 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 140 8 Factor Analysis 141 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 141 A Common Factor Model. . . . . . . . . . . . . . . . . . . . . . . . . . . 142 Identification. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 143 Specifying the Model. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 144 Results of the Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . 145 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 148 9 An Alternative to Analysis of Covariance 149 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 149 Analysis of Covariance and Its Alternative . . . . . . . . . . . . . . . . 149 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 150 Analysis of Covariance. . . . . . . . . . . . . . . . . . . . . . . . . . . . 151 vii Model A for the Olsson Data . . . . . . . . . . . . . . . . . . . . . . . . 151 Identification . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 152 Specifying Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Results for Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 153 Searching for a Better Model. . . . . . . . . . . . . . . . . . . . . . . . 153 Model B for the Olsson Data . . . . . . . . . . . . . . . . . . . . . . . . 155 Results for Model B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 155 Model C for the Olsson Data . . . . . . . . . . . . . . . . . . . . . . . . 157 Results for Model C . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 158 Fitting All Models At Once . . . . . . . . . . . . . . . . . . . . . . . . . 158 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159 10 Simultaneous Analysis of Several Groups 163 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 163 Analysis of Several Groups . . . . . . . . . . . . . . . . . . . . . . . . . 163 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 164 Model B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 172 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 175 11 Felson and Bohrnstedt’s Girls and Boys 179 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Felson and Bohrnstedt’s Model . . . . . . . . . . . . . . . . . . . . . . 179 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 179 Specifying Model A for Girls and Boys . . . . . . . . . . . . . . . . . . 180 Text Output for Model A. . . . . . . . . . . . . . . . . . . . . . . . . . . 183 Graphics Output for Model A . . . . . . . . . . . . . . . . . . . . . . . . 185 Model B for Girls and Boys . . . . . . . . . . . . . . . . . . . . . . . . . 186 viii Results for Model B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 188 Fitting Models A and B in a Single Analysis . . . . . . . . . . . . . . . . 192 Model C for Girls and Boys. . . . . . . . . . . . . . . . . . . . . . . . . . 192 Results for Model C. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 195 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 196 12 Simultaneous Factor Analysis for Several Groups 199 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 199 Model A for the Holzinger and Swineford Boys and Girls . . . . . . . . 200 Results for Model A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202 Model B for the Holzinger and Swineford Boys and Girls . . . . . . . . 204 Results for Model B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 206 Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 210 13 Estimating and Testing Hypotheses about Means 213 Introduction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 213 Means and Intercept Modeling . . . . . . . . . . . . . . . . . . . . . . . 213 About the Data. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 214 Model A for Young and Old Subjects . . . . . . . . . . . . . . . . . . . . 214 Mean Structure Modeling in Amos Graphics . . . . . . . . . . . . . . . 214 Results for Model A. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 216 Model B for Young and Old Subjects . . . . . . . . . . . . . . . . . . . . 218 Results for Model B. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Comparison of Model B with Model A . . . . . . . . . . . . . . . . . . . 220 Multiple Model Input . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 220 Mean Structure Modeling in VB.NET. . . . . . . . . . . . . . . . . . . . 221 ix 14 Regression with an Explicit Intercept 225 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225 Assumptions Made by Amos . . . . . . . . . . . . . . . . . . . . . . . . 225 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 Specifying the Model . . . . . . . . . . . . . . . . . . . . . . . . . . . . 226 Results of the Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . 227 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 229 15 Factor Analysis with Structured Means 233 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 Factor Means. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 233 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 234 Model A for Boys and Girls . . . . . . . . . . . . . . . . . . . . . . . . . 234 Understanding the Cross-Group Constraints . . . . . . . . . . . . . . . 236 Results for Model A . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 237 Model B for Boys and Girls . . . . . . . . . . . . . . . . . . . . . . . . . 239 Results for Model B . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 241 Comparing Models A and B. . . . . . . . . . . . . . . . . . . . . . . . . 241 Modeling in VB.NET . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 242 16 Sörbom’s Alternative to Analysis of Covariance 245 Introduction. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 Assumptions . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 245 About the Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 246 Changing the Default Behavior. . . . . . . . . . . . . . . . . . . . . . . 247 x

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