Practitioner's Guide to Assessing Intelligence and Achievement E-Book

Jack A. Naglieri

• Herausgeber: John Wiley & Sons
• Kategorie: Fachliteratur
• Sprache: Englisch

Seitenzahl: 1272

Veröffentlichungsjahr: 2009

Beschreibung

A complete guide to key intelligence and achievement tests and their effective use The tools used in the assessment process have changed dramatically in recent years. School and clinical psychologists need a comprehensive yet focused resource to which they can turn to learn the basics of key intelligence and achievement tests and how to use them in their assessments of children and adults. With its practical and straightforward presentation, Practitioner's Guide to Assessing Intelligence and Achievement provides that resource. Coedited by two well-known and respected scholars and researchers, Jack Naglieri and Sam Goldstein, the content in this timely book combines traditional and new conceptualizations of intelligence as well as ways to measure achievement. Truly readable and user-friendly, this book provides professionals with a single source from which to examine ability and achievement tests along the same general criteria. Each chapter is written by a leading scholar and test developer and is consistently structured for easy comparison of each test that is examined. Coverage includes: * The theory underlying each test * Description of each test * Tips for administering and scoring each test * Standardization, norms, and reliability of each scale * Practical guidance for the use of each test * Correspondence of each test to IDEA A practical tool designed to aid clinical psychologists in understanding the strengths and weaknesses of the various tests presented, Practitioner's Guide to Assessing Intelligence and Achievement provides students and practitioners with the information they need for their practice and testing efforts to be consistent with recent updates in the field and how those assessment instruments relate to changes in the laws that influence test use.

Leseprobe

Table of Contents

Title Page

Copyright Page

Dedication

PREFACE

Acknowledgements

Foreword

PART I - Introduction

CHAPTER 1 - Understanding the Strengths and Weaknesses of Intelligence and ...

ASSESSING STRENGTHS AND LIMITATIONS OF ABILITY TESTS

INTELLIGENCE TESTS AND THEORIES

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

DIAGNOSIS AND INTERVENTION

INTELLIGENCE TEST BIAS

THE CHANGING FACE OF ACHIEVEMENT TESTING

SUMMARY

REFERENCES

CHAPTER 2 - Current Issues in the Assessment of Intelligence, Specific Learning ...

INTELLIGENCE AND ACHIEVEMENT

ATTENTION DEFICIT HYPERACTIVITY DISORDER

SPECIFIC LEARNING DISABILITY

REFERENCES

PART II - Intelligence Tests Measuring Diverse Abilities

CHAPTER 3 - The Cognitive Assessment System

THEORY UNDERLYING THE CAS

DESCRIPTION OF THE CAS

SIMULTANEOUS SUBTESTS

ADMINISTRATION OF THE CAS

SCORING THE CAS

STANDARDIZATION, NORMS, AND PSYCHOMETRICS OF THE CAS

USE OF THE CAS

VALIDITY OF THE CAS

SUMMARY

REFERENCES

CHAPTER 4 - The Kaufman Assessment Battery for Children—Second Edition

HISTORY AND THEORY OF THE TEST

DESCRIPTION OF THE KABC-II

IDENTIFICATION OF SPECIAL POPULATIONS

FAIRNESS: SEX, RACE, AND ETHNIC DIFFERENCES

SUMMARY

REFERENCES

CHAPTER 5 - Development and Application of the Reynolds Intellectual Assessment ...

THEORY AND STRUCTURE

SCORING AND INTERPRETIVE SOFTWARE

PSYCHOMETRIC PROPERTIES

APPLICATIONS OF THE RIAS

SUMMARY

REFERENCES

CHAPTER 6 - Assessment of Intellectual Strengths and Weaknesses with the ...

THEORY UNDERLYING THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, DEVELOPMENT, AND PSYCHOMETRICS

USES AND INTERPRETIVE STRATEGIES FOR THE SB5

VALIDITY

SUMMARY

REFERENCES

CHAPTER 7 - The Wechsler Intelligence Scale for Children—Fourth Edition

THEORY UNDERLYING THE WISC-IV

DESCRIPTION OF THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND RELIABILITY

USE OF THE TEST

VALIDITY

SUMMARY

REFERENCES

CHAPTER 8 - Woodcock-Johnson III Tests of Cognitive Abilities

THEORETICAL FOUNDATIONS OF THE WJ III

DESCRIPTION

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

STEP-BY-STEP GUIDE TO INTERPRETING THE WJ III COG

SELECTION OF INTERVENTIONS BASED ON TEST RESULTS

VALIDITY

SUMMARY

REFERENCES

PART III - Nonverbal Intelligence Tests

CHAPTER 9 - Comprehensive Test of Nonverbal Intelligence—Second Edition

THEORY UNDERLYING THE CTONI-2

DESCRIPTION OF THE CTONI-2

ADMINISTRATION AND SCORING PROCEDURES

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USES OF THE TEST

VALIDITY

SUMMARY

REFERENCES

CHAPTER 10 - Nonverbal Intellectual and Cognitive Assessment with the Leiter ...

THEORY UNDERLYING THE TEST

DESCRIPTION OF THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, DEVELOPMENT, AND PSYCHOMETRICS

USES AND INTERPRETIVE STRATEGIES FOR THE LEITER-R

VALIDITY

SUMMARY

REFERENCES

CHAPTER 11 - Universal Nonverbal Intelligence Test (UNIT)

THEORY UNDERLYING THE UNIVERSAL NONVERBAL INTELLIGENCE TEST

DESCRIPTION OF THE UNIT

ADMINISTRATION AND SCORING

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

IDENTIFICATION OF SPECIAL POPULATIONS

VALIDITY

THE UNIT IN PRACTICE: A MODEL OF FAIRNESS

SUMMARY

REFERENCES

CHAPTER 12 - Wechsler Nonverbal Scale of Ability (WNV)

INTRODUCTION

DESCRIPTION OF THE WNV

STRUCTURE OF THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE WNV

IDENTIFICATION OF SPECIAL POPULATIONS

VALIDITY

SUMMARY

REFERENCES

PART IV - Achievement Tests

CHAPTER 13 - Basic Achievement Skills Inventory (BASI)

RATIONALE UNDERLYING THE TEST

HISTORICAL INFORMATION

PSYCHOMETRIC PROPERTIES

INTERPRETATION METHODS OF THE BASI-C

TEST SCORES FOR SPECIAL POPULATIONS

SUMMARY

REFERENCES

CHAPTER 14 - Using the Comprehensive Test of Phonological Processing (CTOPP) to ...

RATIONALE UNDERLYING THE CTOPP

DESCRIPTION OF THE CTOPP

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

VALIDITY

SUMMARY

CTOPP-2

REFERENCES

CHAPTER 15 - Dynamic Indicators of Basic Early Literacy Skills (DIBELS)

HISTORICAL PERSPECTIVE AND RATIONALE

DESCRIPTION OF THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

VALIDITY

SUMMARY

REFERENCES

CHAPTER 16 - The Gray Oral Reading Test—Fourth Edition (GORT-4)

RATIONALE UNDERLYING THE TEST

DESCRIPTION OF THE TEST

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

VALIDITY

RELATIONSHIPS BETWEEN TEST SCORES AND STATE CURRICULUM

SUMMARY

REFERENCES

CHAPTER 17 - Kaufman Test of Educational Achievement—Second Edition

RATIONALE UNDERLYING THE TEST

HISTORICAL INFORMATION

DESCRIPTION OF THE KTEA-II

DESCRIPTIONS OF THE KTEA-II COMPREHENSIVE FORM SUBTESTS

ADMINISTRATION AND SCORING

SCORING

USE OF SCORING AND REPORT WRITING SOFTWARE

PSYCHOMETRIC PROPERTIES

VALIDITY

RELATIONSHIPS BETWEEN TEST SCORES AND STATE CURRICULUM

USE OF THE TEST

IDENTIFICATION OF SPECIAL POPULATIONS

INTERVENTIONS BASED ON TEST RESULTS

SUMMARY

REFERENCES

CHAPTER 18 - Wechsler Individual Achievement Test—Second Edition

RATIONALE UNDERLYING THE TEST

DESCRIPTION OF THE TEST

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

STUDIES WITH OTHER TESTS

STUDIES WITH SPECIAL GROUPS

USE OF THE TEST

INTERVENTIONS

SUMMARY

REFERENCES

CHAPTER 19 - Woodcock-Johnson III Tests of Achievement

RATIONALE

DESCRIPTION

ADMINISTRATION AND SCORING

INTERPRETING THE SCORES

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

USE OF THE TEST

INTERPRETATION METHODS

STEP-BY-STEP GUIDE TO INTERPRETING THE WJ III ACH

SELECTION OF INTERVENTIONS BASED ON TEST RESULTS

SUMMARY

REFERENCES

CHAPTER 20 - Achievement Assessment and Progress Monitoring with the Wide Range ...

INTRODUCTION

ADMINISTRATION AND SCORING

STANDARDIZATION, NORMS, DEVELOPMENT, AND PSYCHOMETRICS

TEST USES AND INTERPRETIVE STRATEGIES

TEST SCORES IN SPECIAL POPULATIONS

EVIDENCE OF VALIDITY

SUMMARY

REFERENCES

AUTHOR INDEX

SUBJECT INDEX

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Library of Congress Cataloging-in-Publication Data:

Practitioner’s guide to assessing intelligence and achievement / edited by Jack A. Naglieri, Sam Goldstein.

p. cm.

Includes index.

eISBN : 978-0-470-48816-4

1. Intelligence tests. 2. Achievement tests. I. Naglieri, Jack A. II. Goldstein, Sam, 1952-

BF431.P675 2009

153.9’3-dc22

2008052154

For Andrea, Antonia, and Jack Jr.

JN

For Allyson, Ryan, and Janet.

SG

We dedicate this book to the extraordinary leadership of Alan and Nadeen Kaufman, whose vision for change stimulated the development of the many new tests included in this book and resulted in a significant evolutionary step in the field of assessment. Thanks for your vision of change.

PREFACE

The field of assessment psychology (see Graham & Naglieri, 2003) has changed dramatically since the late 1970s, when we began our careers as psychologists. At that time, there were two well-established options to measure intelligence, the Wechsler (WISC-R) and Binet LM, and a newcomer, the McCarthy Scales of Children’s Abilities. The dominant achievement test was the Wide Range Achievement Test. Matarazzo and Wechsler’s measurement and appraisal of adult intelligence and Sattler’s assessment texts were the main books available. Evolution in the field began with the extraordinary insight of Alan and Nadeen Kaufman and the publication of the Kaufman Assessment Battery for Children (K-ABC). Suddenly, it became apparent that there was great room for improvement in the IQ and achievement tests that we were using to make important decisions about children and adults.

The mid-1980s through the 1990s was a time of change in the field of assessment. Intelligence tests were revised and modified. For example, the Wechsler went from a two-, to three-, to four-dimensional instrument. Theory became increasingly important and efforts were made to apply theory to existing tests. Achievement tests were developed that provided greater coverage of content. IQ tests were challenged by measures of basic psychological processes such as the K-ABC and the Cognitive Assessment System (CAS).

The past 20 years have seen substantial improvements in the quality of psychological and educational tests. Standardization samples that previously had been modest approximations of the U.S. population were now developed with the utmost care and accuracy. Today, estimates of the U.S. population can be made with a level of precision that was not achieved in the 1980s. Not only have we been able to improve the quality of standardization samples, but we have greatly improved the psychometric quality of these tests and developed new approaches to assessment.

The assessment of IQ has expanded to include measures that approach intelligence from a theory-driven perspective. For example, tests that reflect the author’s intention to change from the verbal/nonverbal test content perspective to an organization based on underlying cognitive processes (e.g., K-ABC and CAS) have dramatically expanded the variety of instruments in this area. Additionally, we now have nonverbal measures of general ability specifically designed to better assess culturally and linguistically diverse populations, such as the CTONI, UNIT, and WNV. Similarly, we have more achievement test options, including those that are designed to measure a wide variety of academic skills (e.g., WIAT-II) and those that are more specific (e.g., CTOPP and DIBELS).

As the number of test options in the field has increased, so, too, has the complexity of assessing the utility of these tests, especially for those entering the field. The number of questions about these instruments is wide ranging, with potentially significant consequences. How can a psychologist or educator make informed decisions about which ones meet varying needs in the field? Can we assume that all tests have excellent psychometric qualities? What evidence is there that these various measures are effective for the purposes for which they were developed and used? These and many other questions formed the impetus for this book.

The goal of this book is to provide readers with a single source from which to examine ability and achievement tests along the same general criteria. Chapters are presented in alphabetical order by test name in three groups: (1) intelligence tests with diverse test content, (2) nonverbal intelligence tests, and (3) achievement tests. Each chapter was written from the same outline, typically, by the test’s author(s). The chapters provide the authors an opportunity to illustrate the qualities of their test and the extent to which their particular approach to test development and their test’s characteristics meet the demands practitioners face today and will likely face in the future. We hope this book will allow readers to make informed decisions about the best use of each of these tests.

ACKNOWLEDGMENTS

Thanks to Kathleen Gardner for her editorial assistance and to Isabel Pratt and Lisa Gebo of Wiley for sharing our vision for this volume.

J.A.N. & S.G.

FOREWORD

The clinical assessment of intelligence and achievement is at a crossroads for two reasons. First, there is a marked change in the types of ability and achievement tests that have been published in the past 10 years. Traditional intelligence tests are being challenged by theory-based measures of cognitive processing, and achievement tests that have explicit implications for instruction are being stressed. Second, within the educational arena, the passage of the Individuals with Disabilities Educational Improvement Act (IDEA 2004) in the United States has led many states to determine how to best implement the ambiguous legal guidelines for identifying children with specific learning disabilities (SLD), sometimes passing that decision on to the local districts. Given IDEA, there is considerable controversy about how assessment should change, but it seems clear that the outcomes of these decisions will greatly determine how standardized instruments may be used for SLD diagnosis. To some, standardized assessment of cognitive ability and academic skills is an essential component of a comprehensive assessment; for others, the response-to-intervention method alone is sufficient.

To some professionals in education, standardized assessment of cognitive ability and academic skills served the primary purpose of entering numbers into a discrepancy formula to diagnose SLD. Now that IDEA 2004 no longer mandates identifying an ability-achievement discrepancy to diagnose SLD, some of these professionals are content to rely only on response-to-intervention (RTI) to identify children with SLD. They are happy to kick standardized tests, especially measures of mental processing and cognitive abilities, out the door, without ceremony or fanfare. They would like to see a quick cremation of the diverse instruments that have been developed to measure intelligence, by any definition; and while the door is open, why not get rid of standardized achievement tests as well, because (they argue), what more does anyone need to know about a child’s achievement that hasn’t already been learned during the RTI phase of the evaluation?

Jack Naglieri and Sam Goldstein’s A Practitioner’s Guide to Assessment of Intelligence and Achievement is not targeted for those professionals whose minds are closed to the benefits of standardized tests and who are caught up in the “RTI-only” mantra. Most of the chapters in this book, with all their riches and insights, will do them little good. But A Practitioner’s Guide is a goldmine for professionals who want to understand the individual child or adolescent referred for evaluation and who realize that each student’s unique pattern of strengths and weaknesses provides a dynamic resource for identifying disorders of basic psychological processes and for informing and personalizing interventions. And even the RTI-only people will enjoy Chapter 14, on phonological processing; Chapter 15, on the DIBELS; error analysis on the KTEA-II (Chapter 17); the use of the relative proficiency index (RPI) on the WJ-III Achievement Scale to create appropriate instructional recommendations (Chapter 19); and the systematic treatment of progress monitoring and evaluation of interventions on the BASI (Chapter 13), the Gray Oral (Chapter 16), and the WRAT4 (Chapter 20).

Naglieri and Goldstein are both superstars in the field of assessment who each possess enormous expertise in test development, test research, and clinical practice. My ties to my close friend and colleague, Jack Naglieri, stretch back more than 30 years, to a time when he was my brilliant doctoral student and leader of the graduate-student team that helped Nadeen and me develop the original K-ABC. He subsequently moved the field of assessment forward in a dramatic way when he collaborated with J. P. Das to develop the Luria-inspired PASS theory and the innovative Cognitive Assessment System (CAS). His considerable inspiration and perspiration, sprinkled with an abundance of creativity, reflect a direct translation of the principles that, as a mentor, I have always tried to instill in my graduate students: (1) Scientifically supported practice needs to be rooted in good science; (2) intelligence tests should be based on sound theory, without constraints from the past; (3) new approaches must embrace new technologies while maintaining a healthy respect for the contributions of old technologies; and (4) cognitive and academic assessment, to be truly meaningful, must translate directly to interventions and be fair to ethnic minorities. Sam Goldstein’s considerable contributions via research, writing, test development, and international speaking engagements also reflect these principles, as does A Practitioner’s Guide to Assessment of Intelligence and Achievement.

In the introductory chapter of this book, Naglieri and Goldstein confront the relevance of theory to practice by posing two questions: “But readers may wonder what relevance the underlying conceptualization of a test has? How important is a theory for application in the real world?” These questions are answered briefly in Chapter 1 and extensively in Chapters 3 through 8, which deal with the major cognitive and processing batteries (except for the DAS-II). These chapters are typically coauthored by at least one of the test authors, and they all emphasize the role that theory plays in providing a scientific foundation for the test and in promoting sound theory-based interpretation and application of the profile of scores.

In addition to top-notch coverage of virtually all major comprehensive measures of processes and abilities, A Practitioner’s Guide has many other special features that make it stand out:

• It includes thorough coverage of the major nonverbal measures of cognitive abilities and processing, a topic that frequently does not receive complete coverage despite the key roles played by nonverbal tests for the fair assessment of ELL students, those with hearing impairments, and those who otherwise cannot be tested validly on verbal measures (Chapters 9 through 12, plus the KABC-II Nonverbal Scale in Chapter 4).

• It has the most thorough coverage of the crucial area of achievement assessment that exists anywhere. The achievement test—often the kid brother of the cognitive test that receives little respect or breadth of coverage—is elevated to the forefront of A Practitioner’s Guide. Eight important tests are covered in Chapters 13 through 20, and they are treated in a way that enables readers to understand the integral role that they play for truly understanding the intricacies of a child’s pattern of strengths and weaknesses and the key linkup between processing deficit and specific academic failure. As mentioned earlier, achievement tests that hold great promise for implementing progress monitoring and evaluating scientifically based intervention strategies are covered with the same depth as the more traditional approaches to standardized assessment of academic achievement.

• Chapter 2 deals directly with the IDEA 2004 guidelines, and offers systematic, scientific methods for diagnosing children with SLD that are far more sensible and practical than the crude ability-achievement formula that has dominated the SLD assessment scene since the passage of the Education of All Handicapped Children Act of 1975.

• The chapters are practitioner focused, straightforward, explicit in their instruction to the student, and relevant to new IDEA 2004 requirements, and include pertinent diagrams and figures as well as “tips to remember.” At the same time, each chapter allows for enough instruction to allow students to learn how to use the test, usually from the direct perspective of a test author. Moreover, because the chapters were faithful to the specific topical outline proposed by Naglieri and Goldstein, the chapters contain similar content and organization, facilitating comparisons across tests.

• The topics covered are timely (e.g., IDEA 2004 issues), the chapters are quite readable, and, overall, the book is structured to deal with issues that are most relevant to practitioners, while deemphasizing complex statistical issues.

These features make Naglieri and Goldstein’s A Practitioner’s Guide to Assessment of Intelligence and Achievement an ideal text for the basic course in intelligence testing that is invariably included in the curriculum of graduate training programs for school psychologists, neuropsychologists, and clinical psychologists, especially those courses that include achievement testing alongside cognitive assessment. The book is also well suited to serve as the main source of instruction for graduate (or advanced undergraduate) students’ first course in assessment. These students need to learn the basics of the tests and how to use them. Naglieri and Goldstein’s book does just that, and it does it well. Finally, this volume will serve as a valuable desk reference for new and experienced clinicians.

ALAN S. KAUFMAN Clinical Professor of Psychology Yale Child Study Center Yale University School of Medicine New Haven, CT December 1, 2008

PART I

Introduction

CHAPTER 1

Understanding the Strengths and Weaknesses of Intelligence and Achievement Tests

Jack Naglieri, Sam Goldstein

It is essential that any study and measurement of human intelligence and academic achievement recognize the importance of the brain. The human brain is an amazing organ—a product of an ongoing, six-billion-year construction project. In its physical form and function, the human brain represents millions upon millions of trial-and-error adaptive adjustments. Comprised of an estimated 100 billion neurons and many more glial cells, it is organized into thousands of regions. The human brain, in a seamlessly integrated manner, governs body functions and movement, but more important, it is the seat of intelligence and regulates cognition and achievement. Not surprisingly, although the brains of different animals may not look exactly alike, they all work according to the same principles and mechanisms. These neurons and glial cells communicate using a nearly infinite number of synaptic connections, yet the entire organ in humans weighs only about three pounds. Consider also that an infant is born with a brain of 300 to 400 cm, tripling in size by the adult years. Yet, between birth and the conclusion of the first two decades of life, a nearly infinite acquisition of knowledge and behaviors characterizes human development. Gram for gram, the human brain delivers an almost-dazzling array of motoric, behavioral, cognitive, and emotional capacities nearly impossible to fathom in light of its size.

In her extremely cogent and interesting book, Brain Dance (2004), Dean Falk, a professor of anthropology at Florida State University, describes the conditions and circumstances that allowed a group of ape-like individuals to evolve over a period of at least five million years into Homo sapiens. During this process, the brain became increasingly more specialized, evolving a broad range of abilities as well as right-brain/left-brain and male/female differences. As Falk notes, in less than two million years, brain size doubled in the Homo species, from around 650 cm to 1350 cm. Only a small portion of this newly evolved, larger brain was tied to increasing body size. As Falk points out, this process was unprecedented in the evolutionary histories of other mammals. As brain size increased, neurons enlarged and became more widely spaced and the cerebral cortex became more convoluted. No new structures were found in these larger human brains. However, these larger brains set the foundation for an accelerated evolutionary process never before witnessed in any earthbound, mammalian species. In this process, the prefrontal cortex and the posterior areas of the brain associated with sensory processing in particular became especially convoluted. The shift in neurochemicals, anatomy of neurons, and brain function provided the underlying mechanics of our rapid evolutionary progression, a pattern that was most certainly driven by natural selection.

It is a fascinating historical phenomenon that although scientists and philosophers have written about the intellectual and academic capabilities of the human brain over the last 2,000 years, it is just within the past 100 years, but especially the past 50 years, that we have witnessed an explosion of theories and tests to measure these qualities. This growth has created an often-confusing menu of clinical and educational tools from which to choose. The goal of this book is to help the reader contextualize the strengths and weaknesses of the tests presented and to apply a balanced perspective on their critique. To do so, we asked authors to cover the following 15 essential aspects:

Theory Underlying the Test

1. Historical information, definition of the constructs, and development of the subtests

Description of the Test

2. Subtest background

3. Scales the test yields

4. Structure of the test

Administration and Scoring

5. Tips on administration

6. How to score the test

Standardization, Norms, and Reliability

7. Characteristics of the standardization sample

8. Reliability of the scales

Use of the Test (Including Validity Research on Each Topic)

9. Interpretation methods

10. Identification of special populations

11. Interventions based on test results

Validity

12. Relationships between ability and achievement

13. Fairness, sex, race, and ethnic differences

14. Profiles of abilities and their relationship to diagnosis and treatment planning

15. Factor structure

In this chapter, we review critical points and issues the reader should consider when evaluating the various instruments within the context of the field today and in consideration of what can be reasonably expected for the future. We further urge the reader to carefully examine each author’s contribution with attention to the specific details presented and the extent to which each test addresses the issues that were covered.

ASSESSING STRENGTHS AND LIMITATIONS OF ABILITY TESTS

Traditional tests of intelligence were initiated in 1905 with the publication of the Stanford-Binet and further solidified in 1939 with the publication of the Wechsler-Bellevue Scales. These tests made a substantial contribution to our society, shaped how we define intelligence, and influenced the lives of countless children and adults in the United States and around the world (Anastasi & Urbina, 1997). Even though high-quality intelligence and achievement tests are among the most influential contributions made by psychology to society in general, they have also been the subject of considerable criticism. The value of these tests has been demonstrated by a substantial literature (see Graham & Naglieri, 2002; Jensen, 1998; and Ramsey & Reynolds, 2004) even though there are criticisms that range from emotionally to scientifically based. The strengths and weaknesses of the tests presented in this book should be apparent by the content of each chapter, and especially what information was and was not provided.

In order to best determine the utility of each test, readers should consider the strengths and limitations as reported by the authors or their representatives. One point that needs to be stressed is that sometimes a “limitation” of a test may not be evidenced by lack of empirical evidence or poor quality, but rather by misapplication or misinterpretation of scores. For example, sometimes tests are criticized when they are used for a reason for which they were not developed or intended (e.g., using verbal and performance IQ scores for determining which instructional method to employ). Similarly, some tests are criticized when used in ways for which research suggests the test is ill-suited (e.g., subtest profile analysis). Readers should also consider the source of the criticisms, and the extent to which charges are valid and supported by research findings and not based solely on a critic’s opinion or straw-man arguments.

The information provided in these chapters helps us understand the authors’ position on the most appropriate use of their test. For example, a test such as the Wechsler Nonverbal Scale of Ability (Wechsler & Naglieri, 2006) will not be able to inform us about the examinee’s level of verbal expression and verbal comprehension; it was not developed for that purpose. That is not a limitation of the test itself, but rather an indication of how it should and should not be used. Similarly, using the WISC-IV with an examinee who has limited English-language skills will yield an estimate of ability that, according to Yoakum and Yerkes (1920), will likely be inaccurate because it has been known for nearly 100 years that a person could do poorly on verbal and quantitative tests because of limited skills in English. To avoid “injustice by reason of relative unfamiliarity with English” (p. 19), these persons should be tested with nonverbal measures of general ability (see the tests included in the nonverbal test section of this book). It is important to understand that using a verbal test to measure general ability for someone who does not have an adequate knowledge of English does not mean that the test is invalid. Instead, the score should be interpreted differently (as a measure of English-language comprehension and expression) because of the context within which it was used. The point is, however, that a test of general ability that contains verbal examinations is not inherently faulty, but rather its application to a person who does not speak English undermines the effort to estimate intelligence accurately. Criticisms of the test, therefore, must be viewed within the context of the test’s use.

The limitations of traditional IQ tests containing verbal, quantitative, and performance scales have been recognized by practitioners and test developers in the field. This has led to an effort to provide so-called nonverbal tests of ability, which comprise a substantial portion of this book. These nonverbal tests of general ability represent an effort on the part of test developers to meet the need for a way to measure ability for diverse populations. By measuring ability using tests of general ability that do not involve verbal or quantitative content, the tests offer a specific methodology designed explicitly for assessing diverse populations. That is, nonverbal tests of ability meet a particular need in the field that traditional multicontent tests like the Wechsler and Binet could not adequately address. Just as nonverbal tests of general ability have changed the field, the availability of cognitive processing-based measures of ability has also altered the landscape considerably.

Tests built to measure cognitive processes meet the need for a new approach to assessment that reconceptualizes ability within the context of basic psychological processes. The KABC-II and the CAS stand out as methods of conceptualizing and measuring ability very differently from the verbal/quantitative/nonverbal test content perspective utilized since the early 1900s. These tests are also distinguished from more traditional tests because they were explicitly developed to measure basic psychological processes while avoiding achievement-laden test content. The availability of these tests has also raised the awareness of users and test developers of the need for theoretically-based measures of ability that are appropriate for assessment of culturally and linguistically diverse populations, strongly correlated with achievement, and are linked to intervention. The KABC-II and CAS chapters should be viewed within this larger context and with recognition that theory-based instruments offer considerable advantages.

INTELLIGENCE TESTS AND THEORIES

The field of intelligence testing has evolved considerably over the past 20 years and, most important, the value of having a test that is based in a theory has become much more salient. Although we may discuss the theory behind a test, we often do not reflect carefully upon precisely what this means. According to the United States National Academy of Sciences, in the general population the word theory means a hunch or speculation and is often used as an antonym for a hypothesis or opinion. In contrast, a scientific definition of the word theory “refers to a comprehensive explanation of an important feature of nature that is supported by many facts gathered over time. Theories also allow scientists to make predictions about as yet unobserved phenomena” (Wikipedia, 2008). In the science of assessment psychology, we should use the word theory only to describe a model of a construct that has been tested using scientific experimentation, has demonstrated validity, and can be used to predict future behavior. It is quite important to ask the question, “What theory underlies each of the various ability tests included in this book?”

There is considerable variability in the answers to the question, “What theory was used to describe this test of ability?” For example, the term general intelligence is used to describe tests like the WISC-IV as well as the UNIT, CTONI, and WNV. Some authors merge different views to describe their approach to explaining what the test measures (e.g., KABC-II) and the theory behind the test. Other authors take a much more liberal approach and apply a model to a previously developed test, and still others take a strict approach of building a test explicitly according to one theory (e.g., CAS). Ultimately, it is the responsibility of the test authors to precisely define the idea, model, or theory behind the test, demonstrate the extent to which the test represents their view, and provide evidence for both the approach and its operationalization in that particular test.

Readers may wonder about the relevance of the underlying conceptualization of a test. How important is a theory for application in the real world? Does a test built on a theory offer advantages over one built on an atheoretical basis? Does this really matter? These are the kinds of questions that must be understood in order to effectively use tests of intelligence, ability, or cognitive processing. In our view, understanding the authors’ definition of what their intelligence, ability, or cognitive processing test measures is critical to understanding what the test measures, the relevance that information has for diagnosis and treatment, and how the test will be applied in practice, and especially, explained to teachers and parents.

Readers may wonder what importance a test’s theory holds for the practicing psychologist or the educator. The answer is that theory holds considerable importance to understanding and interpreting the scores from a test. We suggest that (1) the user must understand where each test falls on the continuum between an idea and a theory; (2) if the test was built on a theory, then that theory must be clearly articulated and well understood so that it can be used for interpretation of the test; (3) the validity for the organization of the test must be carefully scrutinized by each and every user; and (4) communication of the findings to consumers must be based on the theory. Why? Because in order to interpret the results from any test, the user must know what the test was designed to measure, whether it does so adequately, and what validity evidence there is for the utility of the constructs. Readers should carefully consider the extent to which this information is provided in each of the chapters.

STANDARDIZATION, NORMS, AND PSYCHOMETRICS

The field of assessment, and especially intelligence and achievement testing, has advanced considerably in the past 25 years to a point where we assume that any test sold by the major companies is well developed, standardized, and normed. The quality of all intelligence and achievement tests is amply described in the chapters contained in this book. Readers should not, however, assume that every test was normed with the same level of sophistication and adequately documented. For example, whereas some of the tests are exemplifiers of excellence, some are less well developed; for example, documentation of the representative nature of the standardization group is inadequate (e.g., DIBELS). Readers should also carefully examine the types of test scores obtained and be cautious of tests that yield only raw scores, which can be misleading (Naglieri & Crocket, 2005). For a review of important psychometric issues, the value of a representative sample, and the statistical characteristics of a test with which the practitioner should be provided, see Naglieri and Chambers (2008) and Urbina (2004).

DIAGNOSIS AND INTERVENTION

Educational diagnosis and eligibility determination are being substantially influenced by the Individuals with Disabilities Education Improvement Act (IDEA) of 2004. This law is having considerable influence on the way school psychologists use intelligence and achievement tests. This law has also influenced community-based decision making in mental health and clinical settings. One of the most important changes particularly relevant to the tests included in this book involves the identification of children with specific learning disabilities (SLD) (see Hale, Flanagan, & Naglieri, 2008; and Hale, Kaufman, Naglieri, & Kavale, 2006), but other issues, such as bias in testing, relevance to intervention, and ongoing treatment monitoring, are also implicated. The issues emphasized in IDEA are included in the chapters contained in this book. For authors of ability tests, this includes evidence of test bias, assessment of basic psychological processes, relevance to identification of SLD, and instructional implications (see KABC-II and CAS). For authors of achievement tests, this also includes relevance to ongoing progress monitoring (see DIBELS and WRAT-PM).

The IDEA and federal regulations have created an opportunity for change in the way school psychologists use ability and achievement tests that will be clear throughout the chapters in this book. Readers should pay particular attention to the similarities and differences among the authors’ methods for applying their tests to the question of SLD diagnosis. For example, the deemphasis of the IQ-Ability test difference (e.g., WISC-IV versus WIAT-II) as a criterion for SLD has led to greater emphasis on tests of basic psychological processes (e.g., K-ABC and CAS) and the need for screening of academic skills (e.g., BASI) and ongoing progress monitoring (WRAT-PM). Test authors are developing methods of assessment that can address the demands of today’s practitioners. For example, the presence of a processing disorder along with learning failure represents the essence of SLD (Kavale, Kaufman, Naglieri, & Hale, 2005). The cognitive processing measures included in this book enable practitioners to document the essential operational marker for SLD—consistency between cognitive deficits and academic deficits coupled with a significant discrepancy between cognitive assets and cognitive deficits (e.g., Hale & Fiorello, 2004; Kavale et al., 2005; Naglieri, 1999, 2000, 2008). One of the most important advantages of this approach is that it unites an identification method with the definition included in IDEA as suggested by Hale, Kaufman, Naglieri, and Kavale (2006). The next step, of course, is the determination of appropriate interventions.

There is considerable controversy about the connection between tests of intelligence and cognitive processing with instruction, perhaps best illustrated by the view proposed by Vellutino, Scanlon, Small, and Fanuele (2003) that tests of ability are irrelevant because they do not predict response to treatment. Some of the chapters in this book provide a view of how instruction can be linked to assessment of cognitive processes and how instruction can be guided by monitoring the academic progress of students on a frequent basis (e.g., DIBELS and WRAT-PM). The extension of assessment information to instruction will likely remain a contentious issue for some time.

INTELLIGENCE TEST BIAS

The characteristics of the U.S. population continue to change and the need for fair assessment of culturally and linguistically diverse populations, especially the Hispanic population, has become increasingly important. IDEA 2004 clearly states that assessments must be selected and administered so as to be nondiscriminatory on a racial or cultural basis. It is critical, therefore, that any measure of ability that is used should have been evaluated for test bias (see Reynolds & Ramsay, 2003, for a summary of test bias issues).

The ability tests presented in the book differ considerably in their conceptualizations and operationalizations of the construct. The two types of tests of general ability (those that include verbal, quantitative, and nonverbal content and those that use only nonverbal test questions) are distinct from the cognitive processing-based measures. Readers should consider the psychometric and impact-related issues related to the scores that these three types of tests yield for various race and ethnic groups. What will become apparent is that while researchers have recognized the value of general intelligence tests with diverse content, these tests yield the largest mean-score race and ethnic differences. When ability is measured using nonverbal tests or conceptualized according to basic psychological processes, both of which avoid the knowledge required to answer verbal and quantitative questions, race and ethnic differences are reduced (Fagan, 2000; Suzuki & Valencia, 1997). Non-verbal and cognitive processing-based tests that do not rely on questions that contain language and quantitative content are, therefore, deemed more appropriate for assessment of culturally and linguistically diverse populations (Fagan, 2000; Suzuki & Valencia, 1997). Importantly, the chapters on nonverbal and cognitive processing tests provide two important approaches that measure ability without the loss of predictive validity and at the same time result in a more equitable system for evaluating culturally and linguistically diverse populations.

THE CHANGING FACE OF ACHIEVEMENT TESTING

The chapters included in this book that cover evaluation of achievement illustrate important changes in the way academic skills are conceptualized and measured. The tests vary in their scope. For example, tests such as the K-TEA and WIAT-II offer measurement of a broad spectrum of skills that are standardized on large samples that represent the U.S. population. These achievement tests also vary in scope. For example, the WJ-III offers a large number of subtests, whereas the WRAT-4 measures relatively fewer areas. The WRAT-4 also provides a way to measure progress over time, as does the BASI, but the BASI provides for both individual as well as group testing options. Tests like the CTOPP and GORT provide specialized measures of achievement. These tests differ in their psychometric characteristics and normative samples, which have important implications for usefulness and defensibility.

SUMMARY

We anticipate that this book will greatly aid users’ understanding of the strengths and weaknesses of the various tests presented. Ultimately, it is the responsibility of the test authors to provide evidence of the quality of their tests and the contexts within which they are most defensibly used. It is the responsibility of the test user to be informed of the various quality issues associated with each test and the interpretive methods the authors recommend. Our goal is, of course, to provide the very best information to the consumers of this information for the benefit of the client.

REFERENCES

Anastasi, A., & Urbina, S. (1997). Psychological testing (7th ed.). Upper Saddle River, NJ: Prentice Hall.

Fagan, J. R. (2000). A theory of intelligence as processing: Implications for society. Psychology, Public Policy, and Law, 6, 168-179.

Falk, D. (2004). Brain dance—revised and expanded edition. Gainesville, FL: University Press.

Graham, J. R., & Naglieri, J. A. (Eds.) (2002). Handbook of assessment psychology. New York: Wiley.

Hale, J. B., & Fiorello, C. A. (2004). School neuropsychology: A practitioner’s handbook. New York: Guilford Press.

Hale, J. N., Flanagan, D. P., & Naglieri, J. A. (2008). Alternative research-based methods for IDEA 2004 identification of children with specific learning disabilities. Communiqué, 36, 14-15.

Hale, J. B., Kaufman, A., Naglieri, J. A., & Kavale, K. A. (2006). Implementation of IDEA: Integrating response to intervention and cognitive assessment methods. Psychology in the Schools, 43, 753-770.

Jensen, A. R. (1998). The g factor: The science of mental ability. Westport, CT: Praeger.

Kavale, K. A., Kaufman, A. S., Naglieri, J. A., & Hale, J. B. (2005). Changing procedures for identifying learning disabilities: The danger of poorly supported ideas. The School Psychologist, 59, 16-25.

Naglieri, J. A. (1999). Essentials of CAS assessment. New York: Wiley.

Naglieri, J. A. (2000). Can profile analysis of ability test scores work? An illustration using the PASS theory and CAS with an unselected cohort. School Psychology Quarterly, 15, 419-433.

Naglieri, J. A. (2008). Best practices in linking cognitive assessment of students with learning disabilities to interventions. In A. Thomas and J. Grimes (Eds.), Best practices in school psychology (5th ed., pp. 679-696). Bethesda, MD: NASP.

Naglieri, J. A., & Chambers, K. (2008). Psychometric issues and current scales for assessing autism spectrum disorders. In S. Goldstein, J. A. Naglieri, & S. Ozonoff (Eds.), Assessment of autism spectrum disorders (pp. 55-90). New York: Springer.

Naglieri, J. A., & Crockett, D. (2005) Response to Intervention (RTI): Is it a scientifically proven method? NASP Communiqué, 34, 38-39.

Ramsay, M. C., & Reynolds, C. R. (2004). Relations between intelligence and achievement tests. In G. Goldstein and S. Beers (Eds.), Comprehensive handbook of psychological assessment (pp. 25-50). New York: Wiley.

Reynolds, C. R., & Ramsay, M. C. (2003). Bias in psychological assessment: An empirical review and recommendations. In J. Graham and J. A. Naglieri (Eds.), Assessment psychology (pp. 67-93). New York: Wiley.

Suzuki, L. A., & Valencia, R. R. (1997). Race-ethnicity and measured intelligence. American Psychologist, 52, 1103-1114.

Urbina, S. (2004). Essentials of psychological testing. New York: Wiley.

Vellutino, F. R., Scanlon, D. M., Small, S., & Fanuele, D. (2003, December). Response to intervention as a vehicle for distinguishing between reading disabled and non-reading disabled children: Evidence for the role of kindergarten and first grade intervention. Paper presented at the National Research Center on Learning Disabilities Responsiveness-to-Intervention Symposium, Kansas City, MO.

Wechsler, D., & Naglieri, J. A. (2006). Wechsler Nonverbal Scale of Ability. San Antonio, TX: Pearson.

Yoakum, C. S., & Yerkes, R. M. (1920). Army Mental Tests. New York: Henry Holt & Company.

CHAPTER 2

Current Issues in the Assessment of Intelligence, Specific Learning Disability, and Attention Deficit Hyperactivity Disorder

Sam Goldstein, Sean Cunningham

In this chapter, we first offer a brief discussion of a number of critical issues concerning the nexus between measures of intelligence and achievement. We then address these tests as they relate to the two most common conditions—attention deficit hyperactivity and specific learning disability—for which they are used to make diagnostic, placement, and treatment decisions.

INTELLIGENCE AND ACHIEVEMENT

Tests of intelligence have traditionally consisted of verbal, quantitative, and nonverbal components. This division was primarily based on practical reasons as opposed to theoretical or scientifically guided principles. Perhaps the first to utilize this model was the Stanford-Binet (Binet & Simon, 1905). The traditional model of intelligence was developed out of the use of the Army Alpha (verbal) and Army Beta (nonverbal) tests during World War I. The Army Alpha and Beta tests were developed, not necessarily to measure different aspects of intelligence, as is the case today with verbal and nonverbal components of intelligence tests, but to be equitable to individuals who did not possess a good understanding of the English language. Individuals who did not have a firm understanding of English were able to take the Army Beta tests and avoid risk of failure that taking the Army Alpha test would provide. The establishment of Army Alpha and Army Beta tests theoretically allowed those giving and taking the tests to be better able to establish an accurate intelligence score. The first comprehensive intelligence test, the Wechsler-Bellevue Scales (Wechsler, 1939), contained a format similar to the Army Alpha and Army Beta tests, combining these divided parts of verbal and nonverbal domains into an overall score of intelligence. Jensen (1998) has demonstrated experimental support for the conceptualization of intelligence as measured by the Binet and Wechsler tests; however, it has been proposed that because these contemporary divisions of intelligence (i.e., verbal, nonverbal) are based on practical circumstances, “the result has been that our [intelligence] tests have been used to define the theory of intelligence the test is intended to measure” (Naglieri, 2008, p. 68).

Contemporary ways to assess intelligence have come under scrutiny, as they have been found to overlap considerably with measures of achievement. Recently, Naglieri and Bornstein (2003) have shown that items used on current measures of intelligence share properties with items from tests of achievement, suggesting a good deal of relatedness between the assessments of the two constructs. In fact, high correlations have been found between measures of intelligence and achievement. In contrast, Rindermann (2007) has suggested that the similarities on scores between the two tests result from one common, latent ability. In examining correlations between different types of intelligence and achievement tests, Rindermann (2007) concluded from a large-scale cross-cultural study that a single latent factor, “general innate cognitive ability,” appears to be responsible for high associations between measures of achievement and cognitive abilities. In addition to this claim, however, Rindermann also noted considerable overlap between the contents of cognitive and achievement measures. This finding appears to offer some explanation for the findings of Naglieri and Bornstein (2003) about the relatedness between scores on intelligence and achievement tests when content overlap is or is not present. It appears, then, that in addition to content overlap, a general underlying ability or dominant latent factor may be responsible for related performance on intelligence and achievement tests as well. Rindermann concludes, “it may not be unreasonable to hypothesize that the cognitive demands and processes involved in solving student achievement test tasks are similar to the ones involved in solving classical intelligence test tasks” (Rindermann, 2007, p. 689).

As a result of the overlap between intelligence and achievement tests, the endorsement of nonverbal tests has gathered recent attention as a unique and fair way to measure intelligence. Nonverbal tests have demonstrated validity in measuring intelligence as exemplified by high correlations with traditional measures of intelligence (Wechsler & Naglieri, 2006). Examples of nonverbal tests include the Naglieri Nonverbal Ability Test (NNAT; Naglieri, 1997, 2003), Wechsler Nonverbal Scale of Ability (WNV; Wechsler & Naglieri, 2006), and the Universal Nonverbal Intelligence Test (UNIT; Bracken & McCallum, 1998). The items that comprise non-verbal intelligence tests are unique in that they do not share the overlap in content with achievement measures. Because nonverbal measures do not share the content overlap with achievement measures, the variance they capture may be more unique to an individual’s intellectual ability. It can be reasonably concluded, then, that non-verbal measures of intelligence provide a more accurate measure of cognitive ability or intelligence when compared to intelligence tests based on a more traditional framework (e.g., division into verbal and nonverbal domains).

Beyond lacking the overlap in content with achievement tests, nonverbal tests of intelligence share additional benefits beyond what more traditional measures of intelligence have to offer. First, nonverbal measures can be administered in group format. Additionally, nonverbal measures of cognitive ability have been demonstrated to be culturally fair, providing similar scores among minorities and individuals with limited English-language skills (Naglieri, 2008; Wechsler & Naglieri, 2006). As a result, nonverbal measures of cognitive ability can work to eliminate the underrepresentation of minorities in gifted and talented programs. Nonverbal measures for gifted minority children have been shown to identify similar percentages of minority children as having the range of scores that would be essential to be identified for gifted programs (Naglieri & Ford, 2003). Furthermore, score discrepancies exist between males and females on traditional measures of intelligence (Lynn, Fergusson, & Horwood, 2005; Lynn, Raine, Venables, Mednick, & Irwing, 2005; Slate, 1998). However, studies have demonstrated that score discrepancies between sexes become less salient as males and females earn the same scores when nonverbal measures are used (Rojahn & Naglieri, 2006).

Because of the previously mentioned benefits of nonverbal measures of ability, researchers have recently proposed that these tests of cognitive ability that stray from the traditional framework (e.g., CAS, K-ABC) offer a better assessment of intellect and demonstrate better clinical utility (Das, Naglieri, & Kirby, 1994; Fagan, 2000; Kaufman, & Kaufman, 2004; Naglieri, 2002, 2003; Naglieri, Goldstein, DeLauder, & Schwebach, 2006). Naglieri (1999) assessed the correlations between several types of intelligence tests and achievement data, finding that tests of intelligence based more on a general intelligence model (e.g., Wechsler scales) correlated less with measures of achievement than cognitively based instruments assessing intellect (e.g., K-ABC, CAS). Similar results have been echoed in other studies (Naglieri & Bornstein, 2003; Naglieri, Goldstein, DeLauder, & Schwebach, 2006; Ramsey & Reynolds, 2003). These results indicate that the cognitively based measures of intelligence may be a more beneficial clinical tool in examining and predicting scores between intellect and achievement. Therefore, they may demonstrate better use in clinical decision-making contexts (e.g., determination of specific learning disability).

A final area to consider when examining traditional models of measuring intelligence with more contemporary measures of ability has to do with testing minority students and students with English as their second language. Individuals possessing a limited understanding of English and/or lack of proper education and subsequent deficiencies in academic skills are likely to have compromised verbal scores on tests of intelligence. Naglieri and Yazzie (1983) demonstrated this phenomenon in a study examining Native American Navajo children living on a reservation. These students spoke English as a second language and performed low on Verbal, but average on Performance Scales of the Wechsler Intelligence Test. As a result, and as previously discussed, the use of nonverbal tests of ability has been proposed as more culturally fair in assessing intelligence in children, suggesting that nonverbal tests are advantages in that they provide a “more equitable evaluation from culturally and linguistically diverse populations” (Naglieri & Ford, 2005, p. 30). Thus, in some ways, concepts of intelligence testing have come full circle over the past 100 years, beginning with the Army Alpha and Beta tests.

ATTENTION DEFICIT HYPERACTIVITY DISORDER

The childhood cognitive and behavioral problems categorized as disorders of attention, impulsivity, and hyperactivity have over the past 50 years presented a clinical challenge for neuropsychologists. The symptom constellation referred to as attention deficit disorder or attention deficit hyperactivity disorder (ADHD) (APA, 2000) has become one of the most widely researched areas in childhood and adolescence with an increasing interest throughout the adult lifespan. Problems arising from this constellation of symptoms have constituted the most chronic childhood behavior disorder (Wender, 1975) and the largest single source of referrals to mental health centers (Barkley, 1990; Gadow, Sprafkin, & Nolan, 2001). In clinic-referred settings, males outnumber females 6 to 1. In epidemiological studies of community-based settings, the ratio is 3 to 1 (Barkley, 2008). The incidence of diagnosis continues to increase with a 70% increase in the diagnosis of children and nearly a 100% increase in the diagnosis of adults between 2000 and 2003 (CDC, 2005). It is now estimated that between 4% and 8% of the population has received a diagnosis of ADHD (CDC, 2005; Cuffe, Moore, & McKeown, 2005). Females are the fastest growing group (Medco, 2005). Broad-based definitions of ADHD find epidemiology of nearly 16% in adults while more narrow definitions report an incidence of 3% to 4% (Faraone & Biederman, 2005). Additionally, incidence has been reported to be higher in populations of individuals with other impairments (Altfas, 2002).

The development of a norm-referenced, psychometric assessment battery specifically designed for ADHD has been an elusive goal for researchers and clinicians. Thus, it is not surprising when reviewing the extensive literature attempting to hypothetically and objectively define specific neuropsychological impairments occurring consistently in children with ADHD that no tried-and-true battery or pattern of impairment comes to light. As Levine (1992) has noted, ADHD symptoms appear to reflect “elusive entities and ... mistaken identities.” The comorbidity issue and the lack of specificity that many tests hold in discriminating ADHD from other disorders further complicates this endeavor. Compromised scores may be due to a variety of causes, leading some researchers to suggest that a profile of test scores be utilized in defining and explaining neuropsychological impairments in children with ADHD (Aylward, Verhulst, & Bell, 1993; Naglieri, 2000). Clinical or laboratory tests alone or in combination have been found to result in classification decisions that frequently disagree with the diagnosis of ADHD when it is based on parent interview, history, and behavior rating scales (Doyle, Biederman, & Seidman, 2000; DuPaul, Anastopoulos, Shelton, Guevremont, & Metevia, 1992). Further, Szatmari, Offord, Siegel, and Finlayson (1990) report that neuropsychological tests appear to distinguish children with ADHD from those with pure anxiety or affective disorders. However, they may not as efficiently distinguish ADHD from other disruptive disorders. These authors concluded that neuropsychological tests were more strongly associated with externalizing than internalizing diagnoses. They appear to correlate with psychiatric symptoms at school but not at home. Additionally, traditional neuropsychological instruments used to infer attention and impulse problems often do not correlate with each other (Naglieri, Goldstein, DeLauder, & Schwebach, 2005). Thus, it is not surprising that Barkley (1991) suggests that when results of the standardized behavior ratings, observations, and history conflict with laboratory measures, the latter should be disregarded in favor of the former as these are considered more ecologically valid sources of data.

Perhaps no other single instrument secondary to continuous performance tests has been touted to be as effective in facilitating the diagnosis ADHD as the Wechsler Intelligence Scale for Children. Researchers have suggested that children with ADHD demonstrate a very different profile from that of normals as well as different profiles across the various subtypes of ADHD (Carlson, Lahey, & Neeper, 1986). Subtests of the Wechsler Intelligence Scale for Children over four editions have been suggested as measures of vigilance and concentration (Gardner, 1979), efficient mental tracking (Lezak, 1983), and divided attention (van Zomeren, 1981). In 1979, Alan Kaufman suggested that the second edition of the Wechsler Scale, Coding, Arithmetic, and Digit Span subtests, factored into an index he referred to as Freedom from Distractibility. Kaufman suggested that the Freedom from Distractibility factor should be at least three points below the verbal and performance factors and that factor scores should not be excessively different from each other as it would be suspected that such a pattern might reflect learning disability.

In 1988, Jerome Sattler suggested that the Arithmetic, Coding, Information, and Digit Span (ACID) subtests on a second edition of the Wechsler provided a profile that could identify attention problems and learning disability. It should be noted that this ACID profile was found in only 11% of a sample of children with ADHD (Wechsler, 1989). The Freedom from Distractibility factor has also not been found to correlate well with observation or parent or teacher reports of ADHD symptoms (Cowen, 1991). Yet children with ADHD demonstrated lower Freedom from Distractibility and Processing Speed indices on the third edition of the Wechsler Intelligence Scale for Children in comparison to Verbal Comprehension and Perceptual Organization index scores, a pattern that differed from the standardization sample (Mealer, Morgan, & Luscomb, 1996; Prifitera & Dersh, 1993). The Freedom from Distractibility factor, however, in the current edition of the Wechsler Intelligence Scale for Children (4th edition), no longer emerges as a single factor. Digit Span and Coding load on separate factors and Arithmetic is an optional test (Wechsler, 2003). Despite these data, Molter (1995) suggested that the differences between the Verbal, Comprehension, and Freedom from Distractibility indices may actually reflect problems related to auditory process or memory rather than ADHD. It is reasonable for the evaluator to heed the advice offered by Anastopoulos, Spisto, and Maher (1993) that evaluators not rely heavily on factors of the Wechsler Intelligence Scale for Children in ruling in or out the diagnosis of ADHD.

It has also been suggested that children with ADHD experience greater problems with sequential rather than simultaneous tasks on the Kaufman Assessment Battery for Children (Carter, Zelko, Oas, & Waltonen, 1990). However, this finding has not been consistently reported. Harvey and Chernouskas (1995) provided preliminary evidence that children with ADHD may present a distinctive pattern of scores on the Woodcock Johnson Psychoeducational Battery. In particular, it was suggested these youth demonstrate problems with basic writing skills, writing fluency, and processing speed. Finally, a number of studies have suggested that measurement of specific intellectual processes may differentiate youth with various subtypes of ADHD (Paolito, 1999; Naglieri, 1999). However, data generated by instruments such as the Cognitive Assessment System (Naglieri & Das, 1997a) are not necessary in making the diagnosis of ADHD but can provide useful information concerning differences in cognitive processes among diagnosed youth.

Although a number of paper-and-pencil tasks have been used over the years in research settings to identify symptoms of ADHD, most have not lent themselves easily to clinical use. In research studies, some of these tests, such as the Matching Familiar Figures Test (Kagan, 1964), appear to have strong positive and negative predictive power for identifying impulsive children. However, in clinical practice such instruments have not proven reliable for confirming the diagnosis of ADHD. Computerized instruments designed to measure sustained attention and the ability to inhibit impulsive responding (Conners, 2008; Gordon, 1993; Greenberg, 1991) have become increasingly popular among neuropsychologists. However, it is important to remember that although these instruments may demonstrate strong positive predictive power (e.g., if the child fails the task, it strongly confirms the presence of symptoms related to ADHD), they possess poor negative predictive power (e.g., if the child passes the task, conclusions cannot be drawn one way or the other concerning the diagnosis) (McGee, Clark, & Symons, 2000). Nonetheless, many evaluators rely on such instruments to provide additional data as part of the diagnostic process rather than a specific data point to confirm or disconfirm the diagnosis of ADHD (Riccio, Reynolds, & Lowe, 2001). The interested reader is referred to Conners (1994) or Homack and Reynolds (2005) for a thorough review of the literature concerning computerized assessment of ADHD.