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  • P1: OTA/XYZ P2: ABCJWST094-fm JWST094-Rasch September 28, 2011 11:13 Printer Name: Yet to Come

    Statistics in PsychologyUsing R and SPSS

  • P1: OTA/XYZ P2: ABCJWST094-fm JWST094-Rasch September 28, 2011 11:13 Printer Name: Yet to Come

    Statistics in PsychologyUsing R and SPSS

    Dieter RaschUniversity of Life Sciences, Vienna, Austria

    Klaus D. Kubinger Takuya YanagidaUniversity of Vienna, Austria

    A John Wiley & Sons, Ltd., Publication

  • P1: OTA/XYZ P2: ABCJWST094-fm JWST094-Rasch September 28, 2011 11:13 Printer Name: Yet to Come

    This edition first published 2011 2011 John Wiley & Sons, Ltd

    Registered officeJohn Wiley & Sons Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United KingdomFor details of our global editorial offices, for customer services and for information about how to apply for permission toreuse the copyright material in this book please see our website at www.wiley.com.

    The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright,Designs and Patents Act 1988.

    All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any formor by any means, electronic, mechanical, photocopying, recording or otherwise, except as permitted by the UK Copyright,Designs and Patents Act 1988, without the prior permission of the publisher.

    Wiley also publishes its books in a variety of electronic formats. Some content that appears in print may not be available inelectronic books.

    Designations used by companies to distinguish their products are often claimed as trademarks. All brand names and productnames used in this book are trade names, service marks, trademarks or registered trademarks of their respective owners.The publisher is not associated with any product or vendor mentioned in this book. This publication is designed to provideaccurate and authoritative information in regard to the subject matter covered. It is sold on the understanding that thepublisher is not engaged in rendering professional services. If professional advice or other expert assistance is required, theservices of a competent professional should be sought.

    Library of Congress Cataloging-in-Publication DataStatistics in psychology using R and SPSS / Dieter Rasch, Klaus D. Kubinger and Takuya Yanagida.

    p. ; cm.Includes bibliographical references and index.ISBN 978-0-470-97124-6 (cloth) ISBN 978-1-119-97964-7 (E-PDF) ISBN 978-1-119-97963-0 (O-book) ISBN

    978-1-119-95202-2 (E-Pub) ISBN 978-1-119-95203-9 (Mobi)1. Psychometrics. 2. SPSS (Computer file) I. Rasch, Dieter. II. Kubinger, Klaus D., 1949- III. Yanagida, Takuya.

    [DNLM: 1. SPSS (Computer file) 2. Psychometricsmethods. 3. Statistics as Topicmethods. 4. Software. BF 39]BF39.S7863 2011150.727dc23

    2011020660

    A catalogue record for this book is available from the British Library.

    Print ISBN: 978-0-470-97124-6ePDF ISBN: 978-1-119-97964-7oBook ISBN: 978-1-119-97963-0ePub ISBN: 978-1-119-95202-2Mobi ISBN: 978-1-119-95203-9

    Typeset in 10/12pt Times by Aptara Inc., New Delhi, India

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    Contents

    Preface x

    Acknowledgments xii

    Part I INTRODUCTION 1

    1 Concept of the Book 3References 11

    2 Measuring in Psychology 122.1 Types of Psychological Measurements 132.2 Measurement Techniques in Psychological Assessment 13

    2.2.1 Psychological Tests 132.2.2 Personality Questionnaires 142.2.3 Projective Techniques 152.2.4 Systematical Behavior Observation 16

    2.3 Quality Criteria in Psychometrics 162.4 Additional Psychological Measurement Techniques 17

    2.4.1 Sociogram 172.4.2 Survey Questionnaires 172.4.3 Ratings 182.4.4 Q-Sort 182.4.5 Semantic Differential 192.4.6 Method of Pair-Wise Comparison 192.4.7 Content Analysis 19

    2.5 Statistical Models of Measurement with Psychological Roots 20References 20

    3 Psychology An Empirical Science 223.1 Gain of Insight in Psychology 233.2 Steps of Empirical Research 26References 29

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    vi CONTENTS

    4 Definition Character, Chance, Experiment, and Survey 304.1 Nominal Scale 354.2 Ordinal Scale 354.3 Interval Scale 374.4 Ratio Scale 384.5 Characters and Factors 40References 41

    Part II DESCRIPTIVE STATISTICS 43

    5 Numerical and Graphical Data Analysis 455.1 Introduction to Data Analysis 455.2 Frequencies and Empirical Distributions 49

    5.2.1 Nominal-Scaled Characters 505.2.2 Ordinal-Scaled Characters 555.2.3 Quantitative Characters 635.2.4 Principles of Charts 735.2.5 Typical Examples of the Use of Tables and Charts 74

    5.3 Statistics 775.3.1 Mean and Variance 775.3.2 Other Measures of Location and Scale 795.3.3 Statistics Based on Higher Moments 91

    5.4 Frequency Distribution for Several Characters 94References 97

    Part III INFERENTIAL STATISTICS FOR ONE CHARACTER 99

    6 Probability and Distribution 1016.1 Relative Frequencies and Probabilities 1016.2 Random Variable and Theoretical Distributions 107

    6.2.1 Binomial Distribution 1096.2.2 Normal Distribution 116

    6.3 Quantiles of Theoretical Distribution Functions 1236.4 Mean and Variance of Theoretical Distributions 1256.5 Estimation of Unknown Parameters 126References 129

    7 Assumptions Random Sampling and Randomization 1307.1 Simple Random Sampling in Surveys 1327.2 Principles of Random Sampling and Randomization 134

    7.2.1 Sampling Methods 1347.2.2 Experimental Designs 140

    References 146

    8 One Sample from One Population 1478.1 Introduction 147

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    CONTENTS vii

    8.2 The Parameter of a Character Modeled by a Normally DistributedRandom Variable 1488.2.1 Estimation of the Unknown Parameter 1488.2.2 A Confidence Interval for the Unknown Parameter 1508.2.3 Hypothesis Testing Concerning the Unknown Parameter 1568.2.4 Test of a Hypothesis Regarding the Unknown Parameter in

    the Case of Primarily Mutually Assigned Observations 1658.3 Planning a Study for Hypothesis Testing with Respect to 1698.4 Sequential Tests for the Unknown Parameter 1798.5 Estimation, Hypothesis Testing, Planning the Study, and Sequential

    Testing Concerning Other Parameters 1838.5.1 The Unknown Parameter 2 1838.5.2 The Unknown Parameter p of a Dichotomous Character 1848.5.3 The Unknown Parameter p of a Dichotomous Character which

    is the Result of Paired Observations 1898.5.4 The Unknown Parameter pj of a Multi-Categorical Character 1928.5.5 Test of a Hypothesis about the Median of a Quantitative

    Character 1958.5.6 Test of a Hypothesis about the Median of a Quantitative

    Character which is the Result of Paired Observations 196References 199

    9 Two Samples from Two Populations 2009.1 Hypothesis Testing, Study Planning, and Sequential Testing Regarding

    the Unknown Parameters 1 and 2 2019.2 Hypothesis Testing, Study Planning, and Sequential Testing for Other

    Parameters 2149.2.1 The Unknown Location Parameters for a Rank-Scaled

    Character 2149.2.2 The Unknown Parameters 21 and 22 2189.2.3 The Unknown Parameters p1 and p2 of a Dichotomous

    Character 2219.2.4 The Unknown Parameters pi of a Multi-Categorical

    Nominal-Scaled Character 2299.3 Equivalence Testing 230References 233

    10 Samples from More than Two Populations 23510.1 The Various Problem Situations 23610.2 Selection Procedures 23710.3 Multiple Comparisons of Means 23810.4 Analysis of Variance 241

    10.4.1 One-Way Analysis of Variance 24110.4.2 One-Way Analysis of Variance for Ordinal-Scaled Characters 26310.4.3 Comparing More than Two Populations with Respect to a

    Nominal-Scaled Character 26510.4.4 Two-Way Analysis of Variance 266

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    viii CONTENTS

    10.4.5 Two-Way Analysis of Variance for Ordinal-Scaled Characters 28910.4.6 Bivariate Comparison of Two Nominal-Scaled Factors 28910.4.7 Three-Way Analysis of Variance 289

    References 299

    Part IV DESCRIPTIVE AND INFERENTIAL STATISTICS FORTWO CHARACTERS 301

    11 Regression and Correlation 30311.1 Introduction 30311.2 Regression Model 30811.3 Correlation Coefficients and Measures of Association 318

    11.3.1 Linear Correlation in Quantitative Characters 31811.3.2 Monotone Relation in Quantitative Characters and Relation

    between Ordinal-Scaled Characters 32511.3.3 Relationship between a Quantitative or Ordinal-Scaled

    Character and a Dichotomous Character 32611.3.4 Relationship between a Quantitative Character and a

    Multi-Categorical Character 33011.3.5 Correlation between Two Nominal-Scaled Characters 33511.3.6 Nonlinear Relationship in Quantitative Characters 345

    11.4 Hypothesis Testing and Planning the Study Concerning CorrelationCoefficients 349

    11.5 Correlation Analysis in Two Samples 357References 360

    Part V INFERENTIAL STATISTICS FOR MORE THAN TWOCHARACTERS 361

    12 One Sample from One Population 36312.1 Association between Three or More Characters 363

    12.1.1 Partial Correlation Coefficient 36512.1.2 Comparison of the Association of One Character with Each

    of Two Other Characters 37112.1.3 Multiple Linear Regression 37212.1.4 Intercorrelations 37412.1.5 Canonical Correlation Coefficient 37712.1.6 Log-Linear Models 377

    12.2 Hypothesis Testing Concerning a Vector of Means 38512.3 Comparisons of Means and Homological Methods for Matched

    Observations 38812.3.1 Hypothesis Testing Concerning Means 38812.3.2 Hypothesis Testing Concerning the Position of Ordinal-Scaled

    Characters 398References 400

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    CONTENTS ix

    13 Samples from More than One Population 40113.1 General Linear Model 40113.2 Analysis of Covariance 40313.3 Multivariate Analysis of Variance 41413.4 Discriminant Analysis 427References 445

    Part VI MODEL GENERATION AND THEORY-GENERATINGPROCEDURES 447

    14 Model Generation 44914.1 Theoretical Basics of Model Generation 449

    14.1.1 Generalized Linear Model 45014.1.2 Model with Latent Variables 453

    14.2 Methods for Determining the Quality and Excellence of a Model 45414.2.1 Goodness of Fit Tests 45414.2.2 Coefficients of Goodness of Fit 45814.2.3 Cross-Validation 462

    14.3 Simulation Non-Analytical Solutions to Statistical Problems 464References 470

    15 Theory-Generating Methods 47115.1 Methods of Descriptive Statistics 471

    15.1.1 Cluster Analysis 47115.1.2 Factor Analysis 48215.1.3 Path Analysis 492

    15.2 Methods of Inferential Statistics 49415.2.1 Further Analysis Methods for Classifying Research Units 49415.2.2 Confirmatory Factor Analysis 50115.2.3 Models of Item Response Theory 506

    References 518

    Appendix A: Data Input 520

    Appendix B: Tables 529

    Appendix C: Symbols and Notation 538

    References 542

    Index 547

  • P1: OTA/XYZ P2: ABCJWST094-Preface JWST094-Rasch September 25, 2011 8:15 Printer Name: Yet to Come

    Preface

    This textbook contains, on the one hand, everything that is needed for a freshman statistician.On the other hand, it can also be used in advanced courses and in particular it can be used forempirical research work.

    Within the Bachelors curriculum it is only possible to demonstrate the correct use of themost important techniques. For the Masters curriculum, however, a certain understandingof these methods is necessary. For doctoral studies, understanding alone is not enough: awillingness to reflect critically on the statistical methods must be developed.

    Since even for doctoral students a repetition of the basics of statistics on an elementarylevel is often useful, with this book they can be picked up individually where their powers ofrecollection end if necessary at the beginning of the Bachelor education. And in contrast,Bachelors students are often interested in the contents of a Masters curriculum or where thetextbook leads. They can get a taste of that now.

    Even lecturers will find something new in this textbook; according to our experience,statistics for psychologists is not taught by professional statisticians but by psychologists,mostly by those at the beginning of their academic careers; anecdotes may at least help themdidactically. These casual reflections can of course also be academically amusing for students.

    Accordingly, the three to four mentioned target groups are guided through the book usingdistinctive design elements.

    All examples given in this textbook refer to psychology as an empirical science. However,the topics covered in psychology are similar to those of (other) social sciences, above allsociology and educational science. So, of course, this textbook suits their framework as well.

    The statistical methods that are recommended in this book and which can be used foranswering the research questions posed by psychology as a science are often only practicablewhen using a computer. Therefore we refer to two software packages in this book. Theprogram package R is both freely accessible and very efficient; that is why we continuouslyuse R here. However, since in psychology the program package IBM SPSS Statistics is stillpreferred for statistical analyses most of the time, it is also illustrated using the examples;here we use version 19.

    We try to present statistical knowledge as simply as possible using these program packages,and avoid formulas wherever reasonable. However, we did not completely avoid formulasbecause we also wish to help those readers interested in the theoretical background. As a

  • P1: OTA/XYZ P2: ABCJWST094-Preface JWST094-Rasch September 25, 2011 8:15 Printer Name: Yet to Come

    PREFACE xi

    matter of fact, more important than formulas is the procurement of appropriate applicationsand interpretations of statistical methods. And that is actually the main focus of this book.

    We have refrained from citing the exact sources for the practical, everyday methods given,reserving that for methods that are new or uncommon.

    With the hope that the reader may easily gather from this textbook all information relevantto his/her individual academic level.

    This book includes an accompanying website. Please visit www.wiley.com/go/statisticsinpsychology

    Dieter Rasch, Klaus D. Kubinger, and Takuya YanagidaRostock and Vienna

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    Acknowledgments

    The authors wish to express their thanks to those who contributed in either the translation orin the programs for this book, especially:

    Dr. Albrecht Gebhardt, Alpen Adria University of Klagenfurth, Austria,who gave us access to the R-package OPDOE and assistance in programming the sequentialtriangular tests.

    In translating the text from German into English we received help from (in alphabetical order):Maximilian Alexander Hetzel, University of Vienna, AustriaNina Heuberger, University of Vienna, AustriaMag. Jurgen Grafeneder, University of Vienna, AustriaMag. Bernhard Piskernik, University of Vienna, AustriaSarah Treiber, University of Vienna, AustriaMag. Alexander Uitz, University of Vienna, Austria

    Because the authors and translators are not native English speakers, w...

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