Cognitive performance of children referred for clinical and … · 2020. 4. 2. · edition...

Cognitive performance of children referredfor clinical and educational diagnoses.

Item Type text; Dissertation-Reproduction (electronic)

Authors Axinn, Dede Susan.

Publisher The University of Arizona.

Rights Copyright © is held by the author. Digital access to this materialis made possible by the University Libraries, University of Arizona.Further transmission, reproduction or presentation (such aspublic display or performance) of protected items is prohibitedexcept with permission of the author.

Download date 25/08/2021 04:43:05

Link to Item http://hdl.handle.net/10150/186941

http://hdl.handle.net/10150/186941

INFORMATION TO USERS

This manuscript has been reproduced from the microfilm. master. UMI films the text directly from the original or copy submitted. Thus, some thesis and dissertation copies are in typewriter face, while others may

be from any type of computer printer.

The quality of this reproduction is dependent upon the quality of the copy submitted. Broken or indistinct print, colored or poor quality illustrations and photographs, print bleedtbrough, substandard margins, and improper alignment can adversely affect reproduction.

In the unlikely. event that the author did not send UMI a complete manuscript and there are missing pages, these will be noted. Also, if unauthorized copyright material had to be removed, a note will indicate the deletion.

Oversize materials (e.g., maps, drawings, charts) are reproduced by sectioning the original, beginning at the upper left-hand comer and

continuing from left to right in equal sections with small overlaps. Each original is also photographed in one exposure and is included in

reduced form at the back of the book.

Photographs included in the original manuscript have been reproduced xerographically in this copy. Higher quality 6" x 9" black and white photographic prints are available for any photographs or illustrations

appearing in this copy for an additional charge. Contact UMI directly to order.

UMI A Bell & Howell Information Company

300 North Zeeb Road. Ann Arbor. M148106·1346 USA 313/761·4700 800:521·0600

Order Number 9517554

Cognitive performance of children referred for clinical and educational diagnoses

Axinn, Dede Susan, Ph.D.

The University of Arizona, 1994

V·M·I 300 N. Zccb Rd. Ann Arbor, MI 48106

COGNITIVE PERFORMANCE OF CHILDREN REFERRED

FOR CLINICAL AND EDUCATIONAL DIAGNOSES

by

Dede Susan Axinn

A Dissertation Submitted to the Faculty of the

DEPARTMENT OF EDUCATIONAL PSYCHOLOGY

In Partial Fulfillment of the Requirements For the Degree of

DOCTOR OF PHILOSOPHY

In the Graduate College

THE UNIVERSITY OF ARIZONA

1 9 9 4

1

THE UNIVERSITY OF ARIZONA GRADUATE COLLEGE

2

As members of the Final Examination Committee, we certify that we have

Dede Susan Axinn read the dissertation prepared by -------------------------------------entitled Cognitive Performance of Children Referred for

Clinical and Educational Diagnoses

and recommend that it be accepted as fulfilling the dissertation

Date

Df. Harl,Y Christia~sen

Q.h&~~M~

1/-1- q« Date

/)- 9- 9/ Date

Date

Date

Final approval and acceptance of this dissertation is contingent upon the candidate's submission of the final copy of the dissertation to the Graduate College.

I hereby certify that I have read this dissertation prepared under my direction and recommend that it be accepted as fulfilling the dissertation requir'e'ment.

~~ ~) \vtS~ )l-1-1~ Digsertation Director ~D-a-te----~--------Dr. Shitala P. Mishra

3

STATEMENT BY AUTHOR

This dissertation has been submitted in partial fulfillment of requirements for an advanced degree at the University of Arizona and is deposited in the University Library to be made available to borrowers under the rules of the Library.

Brief quotations from this dissertation are allowable without special permission, provided that accurate acknowledgment of source is made. Requests for permission for extended quotation form or reproduction of this manuscript in whole or in part may be granted by the head of the major department or the Dean of the Graduate College when in his or her judgment the proposed use of the material is in the interests of scholarship. In all other instances, however, permission must be obtained from the author.

11 J SIGNED: /./Ctf( / "f-e=::;;:""

4

ACKNOWLEDGMENTS

The author wishes to express her sincere appreciation to her committee members and to those who have provided encouragement throughout her doctoral program and during the preparation of this dissertation.

Dr. Shitala P. Mishra, my dissertation chairman, has my enduring respect for inspiring the study and indebtedness for his efforts in proofreading and suggesting meaningful improvements. Dr. Mishra's student focus is evident by his consideration for and popularity among graduate students as a dissertation chair and committee member in our department. Dr. Janiece Lord-Maes has my gratitude for her judicious editorial insights and generous time availability. I am very thankful to Dr. Harley D. Christiansen who is a most compassionate professor and responsible for providing an opportunity for me to assist him in teaching, to excel in psychometrics, and to develop the skills needed to complete the study.

Appreciation is also expressed to Jessie Fryer, Jo Ann Hurley, Rick Haan, and especially, Debbie.

Thanks to a very supportive family, partner, and Perseverance, my goal to earn a doctorate has been achieved. I thank all of you for hanging in there with me.

5

TABLE OF CONTENTS

Page

LIST OF TABLES............................... 7

ABSTRACT. • . • • • • • • • • • • • • • • • • • • • • • • • . • • • • • • • • • • 8

1. INTRODUCTION •••.••••••••••••••••••••••••••••• 9

2. REVIEW OF THE LITERATURE •••••••••••••••••.••• 15

History and Development of Wechsler Scales. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Structure of Wechsler Scales............ 16 WISC-III Content........................ 17 Psychometric Properties................. 20 WISC-III Changes........................ 22 Factor Analysis......................... 23 Individual comparison................... 27 Clinical and Educational Uses of

the wIse-III....................... 28 Group Differences....................... 31 Related Research........................ 33 WISC-III Reviews........................ 34 Summary of Literature................... 36

3. METHOD •••••••••••••••••••••••••••.••••••••••• 38

Sample. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 38 Instrument. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Procedure. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 41 Hypotheses. . • . . . . • . . . . . . . . • . . . . . . . . . • . . . 42 statistical Analysis of Data............ 42

4. RESULTS ..•••••••••.••••••••••••.••••••••••••• 44

Between Group Differences............... 44 Results Related to Hypothesis 1.... 44 Results Related to Hypothesis 2.... 46 Results Related to Hypothesis 3.... 47

Comparison of Underlying Factor Structure................... 49 Results Related to Hypothesis 4.... 49 Results Related to Hypothesis 5.... 53

5. DISCUSSION ...••...•..••....••...•.••......... 61

6

TABLE OF CONTENTS--continued

Page

APPENDIX A: Subtest Comparison Between Groups. . . . . . . . . . . . . . . . . . . . . . . . . . 65

APPENDIX B: IQ Comparison Between Groups.... 67

APPENDIX C: Factor comparison Between Groups. . . . . . . . . . . . . . . . . . . . . . . . . . 69

APPENDIX D: Permission to Reproduce......... 71

REFERENCES. • . • • . . . . . . • . • . . . . . . . • • • • • . . • • • . . . • 73

7

LIST OF TABLES

Table Page

1 WISC-III Factors............................. 24

2 Bannatyne's Recategorizations................ 28

3 Study Participants by Age and Gender......... 39

4 Subtest Means, Standard Comparison and t-ratios for Two Samples ••••.•••••••••••.••• 45

5 Mean IQs, Standard Deviations, t-Ratios for Two Samples.............................. 46

6 Factor Means, Standard Deviations, and t-Ratios for Two Samples ••.••..•.• ~...... 48

7 Comparative Factor Loadings For Sample Groups. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 50

8 WISC-III Factor Structure: Comparison of Study and Normative Samples............... 55

9 Comparison of Factor Loading Patterns for Clinical, Educational, and Norming Samples...................................... 56

10 Coefficients of Congruence Between Z,latching Factors for Two Sample Groups................ 58

11 Coefficients of Congruence Between Matching Factors in Total Sample and Educationally Referred Groups................ 58

12 Coefficients of Congruence Between Matching Factors in Total Sample and Clinically Referred Groups................... 59

13 Coefficients of Congruence Between Matching Factors in Total Sample and Norming Samples.......................... 59

8

ABSTRACT

The Wechsler Intelligence Scale for Children, third

edition (WISC-III) (Wechsler, 1991) was used to compare

cognitive performance of children who were referred for

diagnosis in an educational setting with others referred for

diagnosis in a clinical setting. The WISC-III was

administered to 60 school-aged children in the present

study. An exploratory factor analysis was used to examine

the four-factor structure for both groups of children as

well and compared to the WISC-III norming sample. Factor

analytic results indicated some similarities as well as

differences in the factorial composition of the two groups

of subjects. Factor 1 (Verbal Comprehension) and Factor 3

(Freedom from Distractibility) were found to be similar for

the two groups. No significant differences in the average

performance of the two groups of children were found in

terms of subtest scores, IQs, or factor index scores. The

implications for the use of the WISC-III based on these

results are discussed.

CHAPTER 1

INTRODUCTION

9

Research studies dealing with individual differences in

cognitive abilities among children clearly point to

variations in processing information, solving problems,

comprehending verbal information, perceiving spatial

relationships, and demonstrating social competence

(Bjorklund, 1989). Cognitive style describes the way in

which a person uses her/his capacity and competence to

process information. Once a cognitive style has been

established, educational or clinical intervention can be

tailored to the primary modality of the individual child.

Psychometric assessment has been used to identify

individual and group differences according to various

traits, characteristics, and constructs. Information

obtained from psychological assessments is used in various

settings and for many types of diagnoses. Psychological

evaluations are intended to provide and organize patient

information, provide a common language among professionals,

anticipate treatment outcomes, select intervention methods,

and enhance theoretical understanding of problematic human

behaviors and pathologies (Mezzich & Mezzich, 1987).

Psychological tests are used for many purposes in

educational, clinical, and occupational contexts (Anastasi,

10

1976). Psychometric tools may be administered individually

or to groups of people at a time. Individually administered

tests are preferred by many psychologists over group

administered tests because they provide an opportunity to

observe behaviors during the testing session. Results of

psychological tests have been used to provide guidance in

terms of employment selection, job training, development of

treatment programs, educational placement, and taxonomy

(Anastasi, 1976). Intelligence or cognitive potential is

the most common construct measured. Federal requirements

for special education students (e.g., P.L. 94-142 and P.L.

101-476) make individual intellectual assessment the

foundation of school psychology. The interpretation of

intellectual assessments may qualify or disqualify a student

for special services or funding (Deitz & Repp, 1989).

The most popular individual intellectual assessments

used in schools and clinical settings are the Wechsler

Intelligence Scales (Klausmeier, Mishra, & Maker, 1987).

The Wechsler Intelligence Scale for Children, revised

(WISC-R) (Wechsler, 1974b) was the most frequently used

intelligence test among school psychologists surveyed (Goh,

Teslow, & Fuller, 1981; Hutton, Dubes, & Muir, 1992). The

prominence of the Wechsler tests, especially the WISC-III,

is based on a significant history of improvements,

erudition, psychometric quality, and ease of administration

11

and scoring (Detterman, 1985). Three contrary reviews of

the WISC-III (Carroll, 1993; Shaw, Swerdlik, & Laurent,

1993; Sternberg, 1993) concluded by suggesting the

elimination of the use of the WISC-III.

Children are often referred for intellectual testing as

part of a diagnostic evaluation in clinical and educational

settings. The source of referral may be parents, teachers,

or others. Children may be referred as a result of

perceived intellectual or emotional difficulties or a

combination of problems.

Referral of children by school personnel is often

motivated by academic difficulties. Formal assessment using

intelligence tests helps to discover the child's strengths

and weaknesses. Suggestions for remediation usually focus

on weak areas, while reinforcing strengths. Educational

referrals typically focus on the child's inability to

function in the classroom and/or to keep pace with peers.

The etiology of many referred classroom problems may be

physical, chemical, information processing, behavioral, or

situational. Once a child's strengths and weaknesses have

been identified, an individualized educational program can

enhance academic achievement and classroom performance.

The same procedure for referral, data review,

assessment, interpretation, and intervention are used in all

assessment settings (Cooper, 1982). For children in

12

clinical settings, evaluation using individual intelligence

tests should be part of a diagnostic formulation (Rapoport &

Ismond, 1990). The etiology of problems for children

evaluated in clinical settings may stem from a number of

sources. Each possible source of the child's symptoms must

be examined and eliminated through formal assessment.

Children who are referred for diagnostic evaluation in

clinical settings frequently manifest social and/or academic

problems in the classroom. The intellectual quotient (IQ)

is an important factor in their diagnostic formulations as

well as a good predictor of clinical treatment outcomes

(Harris, 1987).

Overall IQ scores are the starting point for test

interpretation, followed by discrepancies in score

combinations. Meaningful variations are identified and

reviewed from normative and ipsative perspectives. The

pattern of individual intellectual test performance is

evaluated for statistical differences within individual

protocols. Pattern analysis can identify intraindividual

personality and neurological variations and abnormalities,

yet this approach is widely debated (McDermott, Fantuzzo, &

Glutting, 1990). The ipsative differences infer cognitive

strengths and weaknesses. The WISC-III is able to reduce

pairwise comparison from seven comparisons to four with

factor index scores evaluated against the child's mean scale

13

score (Nag1ieri, 1993). Unusual differences are clustered

to discern whether specific groups of children (e.g.,

learning disabled) score in a similar pattern, while

diverging from other specific groups of children.

Hypotheses are generated based on subtest combinations using

factor analytic studies to identify discrete abilities or

influences (Piotrowski & Siegel, 1984). The ability to

differentiate among groups of children based on distinctive

cognitive results may lead to early identification and

preventive intervention. By utilizing the ipsative approach

to test interpretation, normative comparisons are minimized,

thus allowing for a focus on the child's cognitive assets

and liabilities (Zachary, 1990).

Numerous studies have examined pattern analyses of the

Wechsler Intelligence Scales for various groups (Dean, 1978;

Greenblatt, Mattis, & Trad, 1991; Hale & Saxe, 1983;

McDermott et al., 1990; Silverstein, 1984). The WIse-III

successfully differentiated between specific groups of at

risk children in a study by Hishinuma and Yamakawa (1993);

however, further research on the 1991 WISe-III (Wechsler,

1991) is needed.

The purpose of this study was to examine similarities

or differences in cognitive performance of school-aged

children referred for diagnostic evaluations. The

comparison of performance for two groups of individuals was

14

carried out in a different but highly related fashion.

First, an attempt was made to obtain a comparative picture

of the performance of an educationally referred group and a

clinically referred group of children on various subtest

performances. In addition to examination of subtest

performances, three types of IQ scores and factor index

scores obtained from administration of the WISC-III were

compared. Consistent with the overall purpose of the study,

intellectual performance of the sample children also

included a comparison of the factor structure underlying

performance on the WISC-III.

15

CHAPTER 2

REVIEW OF THE LITERATURE

This chapter examines the literature related to the

history, developmental structure, and content of the

WISC-III and reviews the literature as it relates to the

overall purpose of the current investigation. In addition,

the psychometric properties, factor analysis, and clinical

and educational uses of the WISC-III are discussed.

Wechsler intelligence tests are the most researched

children's cognitive assessments (Sattler, 1982), and

empirical investigations have rendered widely divergent

findings. Indeed, the WISC may be both the most endorsed

and most condemned assessment tool (Kamphaus, 1993).

Support for both views is examined in this chapter.

History and Development of Wechsler Scales

The measurement of intelligence has a long history and

continues to be an evolving science. In the 1880s Sir

Francis Galton was the first to measure individual

differences in children. In 1904 Alfred Binet and Theophile

Simon developed the predecessors of current intellectual

assessments (Reynolds, Gutkin, Elliot, & Witt, 1984).

Wechsler's first intelligence test, Wechsler-Bellevue I, was

developed in 1939 to measure the cognitive abilities of

adults. A plethora of research over the past several

16

decades led to the development and downward extensions for

intellectual evaluation of younger people. The Wechsler

intelligence test was revised and expanded to three

versions, Wechsler Preschool and Primary Scale of

Intelligence, Revised (WPPSI-R) (Wechsler, 1989); Wechsler

Adult Intelligence Scale, Revised (WAIS-R) (Wechsler, 1981);

and Wechsler Intelligence Scale for Children, third edition

(WISC-III) (Wechsler, 1991). The Wechsler intelligence

tests are theoretically based on Spearman's (1927) "g"

factor and define intelligence as "the aggregate or global

capacity to act purposefully, to think rationally, and to

deal effectively with his environment" (Wechsler, 1944, p.

3) •

Structure of Wechsler Scales

Wechsler Scales use a variety of subtests to measure

and assess a wide range of abilities, illustrating many

aspects of intelligence (Wechsler, 1991). All Wechsler

intelligence tests divide subtests into two scales, Verbal

and Performance. Each scale produces an IQ, and the

combined average of the Verbal and Performance Scale scores

formulate the Full Scale IQ. Test profiles suggest a

child's strengths and weaknesses although nonintellectual

components also influence test results (Wechsler, 1991).

Wechsler Scales consider intelligence as a global capacity,

and the tests are divided into communication skills and

17

practical abilities. Many diverse subtest areas provide

additional opportunities to evaluate a person's global

cognitive capacity (Wechsler, 1974b). The g factor accounts

for most of the variance in the test and remains an

unrotated factor in factor analysis (Kamphaus, 1993). The

Verbal and Performance Scales do not represent separate

abilities; they are distinct styles applied collectively to

measure intelligence (Wechsler, 1974b).

WISC-III content

The Verbal Scale contains five standard subtests and

one that is optional. The Performance Scale has five

standard and two optional subtests. Raw scores are

converted to scale scores, and IQ and factor indices are

derived from composite scale scores.

Four factor-based index scores are optional provisions

of the WISC-III. The Verbal Comprehension Factor score is

constructed from the scale scores on Information,

Similarities, Vocabulary, and Comprehension subtests. The

Perceptual Organization Factor score is constituted from

scale scores on the Picture Completion, Picture Arrangement,

Block Design, and Object Assembly subtests. The Freedom

from Distractibility Factor score is composed of scale

scores on the Arithmetic and Digit Span subtests. The

Processing Speed Factor score consists of scale scores on

the coding and Symbol Search subtests.

18

The standard subtests on the Verbal Scale are

Information, similarities, Arithmetic, Vocabulary, and

comprehension. Digit Span is an optional Verbal subtest,

and it can be substituted for another subtest as

appropriate. Digit Span is used to measure the child's

immediate auditory recall for number sequences. In the

first section, the child must repeat an increasing number of

digits in the same order as the examiner. In the second

section, the child must recite the digits in reverse order

from the examiner's presentation.

The Information subtest taps the child's long-term

recall for facts and cultural exposure using oral questions

about people, events, places, and objects. The Similarities

subtest requires the child to evaluate the relationship

between things and ideas and to categorize them into logical

groups. Pairs of words are presented for the child to

identify the commonality between them in the Similarities

subtest. The Arithmetic subtest is timed, and the examiner

reads numerical word problems for the child to solve without

the use of pencil and paper. The final six Arithmetic items

are read by the Child, and bonus points are awarded for

correct responses given within ten seconds. The Vocabulary

subtest evaluates the child's ability to define and express

the meaning of words. This subtest is considered the best

indicator of Verbal ability (Sattler, 1988). The

19

Comprehension subtest assesses the child's ability to solve

practical problems using social judgment and common sense

reasoning. On many Verbal subtests, only specific responses

may be queried.

The standard subtests on the Performance Scale are

Picture Completion, Coding, Picture Arrangement, Block

Design, and Object Assembly. The Picture Completion subtest

taps a child's visual memory, attention to visual detail,

and understanding of content quality. Illustrations are

presented with a relevant detail omitted for the child to

point out. The Coding subtest requires the ability to learn

nonverbal material, as well as visual memory, visual motor

speed, and coordination. The child must copy symbols that

have been paired with geometric shapes or numbers, and the

score is determined by the amount completed within a time

limit. The Picture Arrangement is a timed subtest that

employs sequential planning ability, distinguishing relevant

details, and anticipation of social outcomes. Each item in

Picture Arrangement presents a series of pictures for the

child to rearrange in the appropriate sequence. The Block

Design is a timed subtest which measures a child's

perceptual organization of abstract figures constructed from

parts and spatial processing ability. object Assembly is

also a timed subtest, which assesses the ability to

recognize and assemble parts of a whole picture. Success on

20

this subtest requires adequate spatial relations,

visual-motor coordination, and persistence. Children of all

ages are given every item on the Object Assembly subtest.

Symbol Search and Mazes are both optional subtests

which require the psychometrician to time the child's speed

in task completion. The Mazes subtest evaluates problem

solving and the ability to follow a visual pattern within a

time limit. In a series of mazes, the child must trace a

line from the center of the maze to the exit without going

through lines or entering blocked pathways. In the Symbol

Search subtest, the child must visually scan two sets of

symbols and determine whether the symbol in the target group

appears again in that row of symbols.

Psychometric Properties

Across all age groups, the average reliability

coefficients of WISC-III subtests, IQ, and factor scores in

the WISC-III Manual range from .76 on Picture Arrangement to

.96 on the Full Scale IQ. However, for individual subtests,

age-specific reliability coefficients plummet to .60 on

Object Assembly for 14-year-olds. No individual reliability

coefficient on subtests exceeds .92 (Block Design for age

15). IQ reliability coefficients range from .89

(Performance IQ, age 14), to .97 (Full Scale IQ, age 14).

Factor index coefficients are lower, ranging from .80

(processing Speed, age 7), to .95 (Verbal Comprehension,

21

ages 12,14 and 15). (See WISC-III Manual for additional

information.)

WISC-R subtest composites have good reliability;

however, age-related differences exist. Verbal subtests

tend to have.higher reliability than Performance subtests.

Greater reliability is established as factors include more

subtests (Piotrowski & Siegel, 1984). Kaufman (1993) found

that subtest stability and reliability decreased from the

WISC-R to the WISC-III; however, Bracken, McCullum, and

Crain (1993) reported that the revised edition had higher

subtest composite reliabilities.

Construct validity is demonstrated with factor analytic

evidence, correlation with other cognitive assessments, and

scholastic performance. WISC-III construct and

criterion-related validity were evident with at-risk

students (Hishinuma & Yamakawa, 1993) as well as with

hearing- impaired children (Maller & Branden, 1993). There

was significant predictive and discriminant validity between

the WISC-III and Woodcock-Johnson Psycho-Educational

Battery-Revised (W-J-R) (Woodcock & Mather, 1989) for

seriously emotionally disturbed youth (Teeter & Smith,

1993). The significant correlation between the WISC-III and

the WISC-R supports the validity of the current version,

through a history of extensive empirical studies. Between

WISC-R and WISC-III administrations, concurrent validity

22

studies provide evidence of .89 correlation for the Full

Scale IQ scores (Wechsler, 1991). The WISC-III Manual

confirmed the criterion-related validity of the factor

structure with small clinical groups (Wechsler, 1991).

(Refer to WISC-III Manual for more information.)

Prewett and Matavich (1994) compared test results of

the WISC-III and the Stanford-Binet Intelligence Scale,

Fourth Edition (S-B IV) (Thorndike, Hagen, & Sattler, 1986b)

and found lower scores on the WISC-III, thus suggesting

different diagnoses.

WISC-III Changes

Notable improvements between the WISC-R and the revised

WISC-III included more extensive standardization and the

provision of four racial/ethnic classifications instead of

two. The WISC-III standardization was stratified according

to the 1988 United states Census according to age, gender,

ethnicity, geographic region, and parental education level.

The proportions of race, gender, region, and parent

education were maintained in each age group. The 2,200

children assessed formed 11 age groups and were divided into

four national regions. Each age group was represented by

200 children. pilot studies were conducted to ensure

standard scoring criteria. Examiners were trained, and

interrater reliability was controlled using

computer-generated feedback to identify discrepancies.

23

The WISC-III altered items and added color yet kept the

dual-scale format of its 1949 and 1974 prototypes. The

WISC-III retained approximately 70% of the items from the

WISC-R. changes included extended basal and ceiling items,

altered scoring criteria, sequence of subtest

administration, and a new subtest, Symbol Search. The

Symbol Search subtest was developed to augment the Freedom

from Distractibility Factor; however, factor analysis

methods proved that it created a separate factor (Wechsler,

1991). The WISC-III increased the number of items on 10

subtests to extend the basal and ceiling levels. As a

result the scoring criteria were more objective, and the

placement of the scoring criteria in the administration

section was more convenient. The color and increased size

of some visual stimuli were attractive and had better racial

and gender balance (Kaufman, 1993).

Factor Analysis

Factor- analysis is used to distinguish constructs that

characterize the association among sets of interconnected

variables (Shavelson, 1988). The amount of variance between

two sets of IQ scores is measured by factor loadings

(correlations) (Kline, 1991). Factors cluster in various

combinations to identify a specific construct, but

equivalent samples can cluster differently. When a limited

number of factors are considered, this statistical analysis

24

simplifies complex data. The size of the shared factors is

measured by eigenvalues (Kline, 1991). Eigenvalues range

from zero to V (V = number of variables in the factor

analysis). The conventional eigenvalue criterion in social

science analyses is set at 1.0 (Sattler, 1982); however,

this level may not be stringent and appropriate (Roid,

Prifitera, & Weiss, 1993).

Intelligence tests, particularly the WISC-III, provide

more information than the intelligence quotient score.

Kaufman (1975) identified three interpretive factors on the

WISC-R: Verbal Comprehension, Perceptual Organization, and

Freedom from Distractibility. In addition, Processing

Speed, derived from one new subtest, Symbol Search, and a

retained subtest, Coding, were added to the WISC-III

(Wechsler, 1991) (see Table 1).

Table 1

WISC-III Factors

Factor 1 Factor 2 Factor 3 Factor 4

(Verbal (Perceptual (Freedom from (Processing Comprehension) Organization) Distractibility) Speed)

Information Picture Completion Arithmeti~ Coding

Similarities Picture Arrangement Digit Span Symbol Search

Vocabulary Block Design

Comprehension Object Assembly

25

Despite variations in theoretical perspectives and

statistical methodology, Kaufman's (1975) three main factors

emerge in Wechsler's Scales (silverstein, 1986). A strong

Verbal Factor, a lesser Performance Factor, and a weak

Memory/Freedom from Distractibility Factor are established

(Matarazzo, 1972). The third factor, Freedom from

Distractibility, may help in the interpretation of

discrepancies between Verbal and Performance scores

(Kaufman, 1979).

The Verbal Comprehension Factor is intended to

represent verbal capacity and mental processing

comprehension (Sattler, 1988). The Perceptual Organization

Factor theoretically evaluates a child's discrimination of

visual stimuli and processing arrangement skills (Sattler,

1988). The intent of the Freedom from Distractibility

Factor is to measure concentration and sustained attention

(Sattler, 1988). The Symbol Search subtest was developed to

enhance the Freedom from Distractibility Factor. It is

considered to measure visual processing speed but has a

higher factor loading on Perceptual Organization than the

Coding subtest (Kamphaus, 1993). The Processing Speed

Factor hypothetically evaluates the amount of time required

to evaluate and solve problems visually.

26

The interpretation of these Verbal to Performance

discrepancies is the most common factor analysis of Wechsler

Intelligence Scales (Kaufman, 1976). Discrepancies on 11

points are common in the general population and correspond

with familial education and vocation (Sattler, 1982).

Kaufman's (1975) Verbal Comprehension and Perceptual

organization Factors loosely parallel Wechsler's Verbal and

Performance Scales. The third factor, Freedom from

Distractibility, contributes the least amount of variance in

WISC-R factor analysis (Reschly, 1978).

There are many problems associated with factor

analysis; providing impractical statistical abstractions

rather than augmenting clinical intervention is particularly

troublesome (Heim, 1975). Disparate findings result from

various methodological flaws (Cattell, 1978). Differences

in results using the same data set may be caused by the

formula used in factor analysis, number of factors

considered, and the infinite number of possible rotations.

In addition, the nomenclature of factors may distort

understanding of the variables (Bracken et al., 1993).

Stedman, Lawlis, Cortner, and Achterberg (1978)

reported that the WISC-R test factors were not discrete, and

nonverbal factors contributed to the Perceptual Organization

Factor. Extreme variability can distort large differences

among subtest scores, scale, or factor scores because they

27

are established by a mean. Many educationally placed

children score three or more points lower on Freedom from

Distractibility than on Verbal Comprehension or Perceptual

organization Factors (Kaufman, 1979).

Individual Comparison

A five-point hierarchical analysis of test results is

recommended (Sattler, 1982), where the broadest factors are

evaluated to interpret a child's score before examining

lower-order factors (Truch, 1993). The suggested order of

interpretive analysis is IQ scores, factor indices, high and

low subtest scores, subtest pattern, and response styles.

One purpose of pattern analysis is to identify

personality and neurological abnormalities and to

differentiate among separate homogeneous groups. The

diagnostic utility of pattern analysis is disputed among

psychologists (Sattler, 1974). Pattern analysis uses

simultaneous comparisons to provide clusters of statistical

inference, yet the problems involved with multiple

comparisons must be avoided (Silverstein, 1982). Subtest

scatter is another type of pattern analysis used for

intellectual assessments. The average subtest scatter on

the WISC-R was 9.7 scale score points for children in the

norming sample (Kaufman, 1976). Bannatyne's (1974)

clustering of subtests, provides a common pattern analysis

(see Table 2). Bannatyne's (1974) cluster analysis groups

Table 2

Bannatyne's Recategorizations

Conceptual

Similarities

Vocabulary

Comprehension

Spatial

Picture Completion

Block Design

Object Assembly

Sequencing

Arithmetic

Digit Span

Coding

28

Acquired Knowledge

Information

Arithmetic

Vocabulary

WISC subtests into four factors: conceptual, Spatial,

Sequencing, and Acquired Knowledge. Bannatyne's

recategorization is also applied to the WISC-III (Truch,

1993).

Intra-subject test comparison loses 60% of WISC-R

reliability variance (McDermott et al., 1990). Significant

statistical differences on WISC-R profiles did not enhance

identification of groups of children (Miller, 1980).

Profiles with broad subtest scatter should be interpreted

with caution (Blaha & Wallbrown, 1984). WISC-R profile

analysis was unable to predict children's achievement in

reading and arithmetic (Hale & Saxe, 1983).

Clinical and Educational Uses of the WISC-III

Some theorists dispute the diagnostic utility of

profile differences on the WISC-R (Sattler, 1974). In 1939,

Wechsler identified emotional factors from performance on

29

individual subtests. Intellectual assessments are designed

to measure cognitive ability, although personal response

styles reveal an individual's strengths, weaknesses, and

emotional characteristics (Wechsler, 1941).

Despite a very high correlation between the WISC-III

and the WISC-R, scores tend to be lower on the more recent

versions (sternberg, 1993). Larrabee and Holroyd (1976)

found lower scores on the WISC-R compared to the original

WISC (Wechsler, 1949). Lower scores impact placement

decisions and result in more mentally handicapped children

being placed in special education classes (Dumont & Faro,

1993a). Such placements can manifest in social

stigmatization and negatively affect school district

budgets. In contrast fewer children are likely to qualify

as learning disabled using the WISC-III because the

discrepancy between achievement and ability scores is

reduced (Post & Mitchell, 1993). A triennial comparison of

educationally referred students tested using the WISC-R and

the WISC-III found a smaller score differential between the

two over the period, and lower scores were more frequent on

the Performance IQ for both versions (Graf & Hinton, 1994).

Dyslexic children's Verbal IQ was five points lower upon

WISC-R to WISC-III retest; however, there was no significant

change on Performance IQ scores (Newby, Recht, Caldwell, &

Schaefer, 1993). Average score differences between the

30

WISC-III and the WISC-R were significantly greater for black

than white children (Graf & Hinton, 1994).

Although the WISC-III attempted to remove biased items,

(Dumont & Faro, 1993b), it remains culturally entrenched and

verbally laden (Kaufman, 1993). The elimination of

emotionally provoking items on the WISC-III also diminished

Wechsler's goal of augmenting clinical interpretation

(Kaufman, 1993). Lower Performance scores may be attributed

to visual distraction resulting from adding color to the

Picture Completion and Picture Arrangement subtests (Graf &

Hinton, 1994).

Barona (1989) reported that the pattern of WISC-R

factors affecting special education qualification decisions

was similar for learning disabled, mentally retarded, and

ineligible students from three major ethnic groups. The

WISC-R factor structure was analogous among Anglos, blacks,

Chicanos, and Papagos (Reschley, 1978). Weiss, Prifitera,

and Roid (1993) demonstrated WISC-III predictive validity

across gender and ethnic groups. Different processing modes

were evidenced between gifted and learning disabled Navajos

on the WISC-R (Mishra, Lord, & Sabers, 1989). However, no

distinct profiles emerged for learning disabled

Mexican-American (Mishra, 1984a) or Papago Native American

(Mishra, 1984b) children. The'WISC-III Verbal IQ and Full

Scale IQ scores were approximately one standard deviation

31

below the mean for Tohono O'odham children, thus making few

eligible to meet state criteria as learning disabled

(Tanner-Halverson, Burden, & Sabers, 1993).

Group Differences

David Wechsler (1974a) hypothesized that significant

discrepancies between Verbal and Performance scores

indicated psychopathology. Higher Verbal scores were

expected among psychiatric patients diagnosed with neurotic,

psychotic, or organic conditions. Juvenile delinquents and

persons with mental retardation were expected to score

higher on the Performance subtests. wechsler compiled test

profiles to distinguish characteristics for five clinical

groups. He found that Block Design subtest scores were

lower for subjects with organic conditions, while

Similarities subtest scores were depressed among mentally

retarded persons (Wechsler, 1941). Unique psychometric

patterns were discernible for schizophrenic children on the

WISC, identifying 40% of schizophrenic children with a 2%

error rate (Wechsler & Jaros, 1965). More than half of that

sample had significant scale score divergence from the mean

on three subtests (Wechsler & Jaros, 1965). Specific

WISC-III subtest patterns were more frequent in profiles of

children diagnosed with learning disabilities and attention

deficit hyperactivity disorders than in profiles of children

in the norming sample (Prifitera & Dersh, 1993). Moreover,

32

students diagnosed with attention deficit hyperactivity

disorder had a significantly lower Processing Speed Factor,

Freedom from Distractibility Factor, and Verbal IQ scores

than the standardization group but higher Perceptual

Organization Factor scores (Schwean, Saklofske, Yackulic, &

Quinn, 1993).

The factor structure of the WISC-R was similar in a

comparison of psychiatric and normal children (Culbert,

Hamer, & Klinge, 1989; Hodges, 1982). Equivalent factor

structure was confirmed in a study with psychiatric and

normal adults on the WAIS-R (Beck, Horwitz, Seidenber,

Parker, & Frank, 1985; Atkinson & Cyr, 1984). Perceptual

integration was lower among learning disabled children,

while emotionally disturbed children scored lower on verbal

sections of the WISC-R (Dean, 1978). A lower ACID profile

(Arithmetic, Coding, Information, and Digit Span subtests)

was common for children with learning problems (Truch,

1993). There was no specific ACID pattern found in an

investigation of a child psychiatric population (Greenblatt

et al., 1991). Th.e ACID profile may be useful for

generatin9 hypotheses, although it cannot diagnose

educational problems (Truch, 1993). The results of the

Digit Span, Coding, and Mazes subtests are often disparate

from the trend established by other subtests (Kamphaus,

1993).

33

Research using Digit Span indicates that the subtest

measures more than short-term memory (Mishra, Ferguson, &

King, 1985). Neurological dysfunction may be apparent from

different abilities required in Digit Span Forward and Digit

Span Backward~ Developmentally delayed children with right

cerebral hemisphere deficits produce significantly higher

scores on Digit Span Forward than Digit Span Backward (Rudel

& Denckla, 1974). Digit Span has a .85 factor loading for

Freedom from Distractibility, but no intercorrelation is

listed for the Full Scale IQ (Wechsler, 1991). The Digit

Span subtest has the highest specificity value and evaluates

a unique ability (Kamphaus & Platt, 1992).

Related Research

Both support and opposition to using IQ tests,

specifically of the WISe-III, are justified. Objections to

intellectual assessments include arbitrary school placements

based on test results, following a medical model of illness,

racial and/or ethnic biases, and inaccurate prediction of

future behavior (Branden & Reschly, 1993). Wechsler scores

are not ratio scales; the absence of a zero point allows for

only simple comparison to determine an individual's

cognitive performance (Truch, 1993). Responding to his

opponents' arguments, Wechsler (1974a) stated that IQ is a

numerical ratio, identifying relative abilities by comparing

an individual score to the average score for his/her age

34

cohorts. Moreover, the use of a deviation IQ in Wechsler

Scales reduces some IQ psychometric problems (Zimmerman &

Woo-Sam, 1985). The use of Wechsler's IQ tests is further

justified by demonstrating significant correlations between

IQ and academic achievement and between Wechsler

Intelligence Scales and other IQ tests.

WISC-III Reviews

The revised WISC-III has received both support and

criticism from psychologists. According to Carroll (1993),

the WISC-III produced insufficient improvements, especially

in factor indices, to justify its popularity. The allure of

Wechsler intelligence tests may be attributed to its simple

administration procedures, yet its greatest weakness is that

results are explained in terms of only one index (Detterman,

1985).

Verbal Comprehension and Perceptual Organization are

significant factors on the WISC-III; however, Freedom from

Distractibility and Processing Speed have not been proven to

be discrete (Carroll, 1993). Freedom from Distractibility

and Processing Speed Factors have small factor loadings.

Hence, further investigation is warranted, and caution is

recommended in interpretation (Kamphaus, 1993). Kaufman

(1993) predicted that the Processing Speed Factor will soon

be obsolete.

35

WIse-III factor stability confirmed the factor

structure in the standardization sample in a study by Roid

et ale (1993). Processing Speed was more robust than

Freedom from Distractibility, and Sattler (1992) found that

the third and fourth factors were not significant for 4 of

the 11 age groups. Sattler's (1992) findings were

challenged by Roid et ale (1993), who claimed that setting

the eigenvalue criterion at 1.0 invalidated pertinent

statistical methodology. The third and fourth factors were

easily misinterpreted because they were derived from only

two subtests and contributed a minimal amount of total test

variance (Dumont & Faro, 1993b). Mean factor scores on

Freedom from Distractibility and Processing Speed were low

for children referred for evaluation in clinical settings

(Wechsler, 1991).

There is no concomitant intellectual theory to support

the new WISe-III factors, as required for adequate test

construction (Kamphaus, Benson, Hutchinson, & Platt, 1994).

Factor index scores aid test interpretation but should not

be reported. The WISe-III cannot diagnose clinical or

emotional illness or dyslexia (Truch, 1993).

Prewett and Matavich (1994) reported dissimilar

classifications based on a comparison of WISe-III and S-B IV

(Thorndike, Hagen, & Sattler, 1986a), with WIse-III scores

averaging 9.4 points lower. Emotionally disturbed children

36

earned WISC-III factor scores similar to those of the

Woodcock-Johnson Psychoeducational Battery, Revised edition,

reasoning scores (Teeter & smith, 1993).

Summary of Literature

Wechsler Intelligence Scales share a rich history and

wide popularity in the measurement of cognitive abilities.

The Psychological Corporation (1991) sUbstantiated adequate

reliability and validity of the WISC-III. This finding

contrasts with lower IQ scores reported on the WISC-III than

the WISC-R (Sternberg, 1993) and lower scores than the S-B

IV produces (Prewett & Matavich, 1994). Considerable effort

is apparent in the WISC-III standardization, and the current

version retains 70% of WISC-R items.

Factor analysis is a statistical procedure used to

identify related constructs. Kaufman (1975) identified

three main factors on the WISC-R; the WISC-III identifies

four factors. No theoretical foundation preceded the

development of the four factors. The new subtest, Symbol

Search, was developed to load on the Freedom from

Distractibility Factor; however, factor analysis results

find it to be unrelated. The investigation of factor

structure may provide numerical abstraction rather than

augmenting clinical diagnosis and intervention.

The literature on the ability to distinguish among

specific groups based on Wechsler Intelligence test scores

37

has been inconsistent. More comparative studies are needed

to evaluate the WISC-III fully. The literature has been

generally supportive, although it remains divided on the

merits of the WISC-III.

CHAPTER 3

METHOD

38

This chapter provides a detailed description of the

methodology used for the substantiation of major hypotheses

of the study. In doing so, various components of

methodology such as sampling procedure and sample, data

collection procedure, statement of major hypotheses,

instrumentation, and statistical analyses are described.

Sample

The 60 participants selected for the study were

referred for psychological assessments from a clinical and

an educational setting. All subjects between the ages of 6

years 3 months and 16 years 10 months who were referred for

diagnostic evaluations were sampled from a small school

district and a Rocky Mountain child psychiatric facility.

Children referred for diagnostic evaluation in two locations

were matched by age, and use of this process resulted in a

sample of 60 subjects. From the pool of children referred

for evaluation, 30 came from an educational setting, and the

re~aining 30 were referred in a clinical environment. It

should be noted that although no systematic attempt was made

to obtain gender balance in this sample, the sampling

process used in this study resulted in a very close gender

match. The referred participants included 23 males from the

39

educational setting, 20 males from the clinical setting, 7

females from educational environment, and 10 females from

the clinical environment. Characteristics of sample

subjects are summarized in Table 3.

Table 3

study Participants by Age and Gender en = 60)

Education (n = 30) Clinical (n = 30)

Age Groups Male Female Male Female

6 - 6.11 1

7 - 7.11 4 1 5

8 - 8.11 3 3

9 - 9.11 3 1 3 1

10 - 10.11 1 1

11 -11.11 2 1 2

12 - 12.11 1 1

13 -13.11 4 1 4 1

14 - 14.11 2 2

15 - 15.11 4 2 2

16 - 16.11 1 1

23 7 20 10

40

All children in both settings were evaluated by the

same certified professional who was trained and supervised

in the administration of psychological tests. The

assessments were administered according to the standard

procedures outlined in the WISe-III Manual (Wechsler, 1991).

In the educational setting, referrals were either

federally mandated re-evaluations for special education

eligibility or parent or teacher referred based on

scholastic and/or behavioral concerns. The special

education secretary provided the psychometrist with a list

of students to be assessed as scheduling allowed. Most

evaluations took approximately two hours, and all were

performed individually in a quiet office setting.

The clinically referred children, with psychological

diagnoses such as major depression and conduct disorders,

were in-patients at a child psychiatric facility. Generally

these children were referred as a result of their parents

concerns, although some were referred from outpatient

therapists, and others were admitted after a suicide

attempt. All children admitted were given complete

diagnostic formulations by a team of professionals in

various specialty areas. Within a day or two after

admission, subjects were psychologically evaluated in a

quiet office setting for approximately three hours.

41

Instrument

The WISe-III is an individually administered test of

children's cognitive abilities developed for children

ranging in age from 6-0 to 16-11. Cognitive abilities are

measured by subtest raw scores and converted into scale

scores. Subtest scale scores range from 1 to 19 with a mean

of 10, and a standard deviation of three. The sum of

subtest scale scores comprise three composites, the Verbal

IQ, Performance IQ, and Full Scale IQ. The Full Scale IQ

score is obtained by averaging the Verbal and Performance

IQs. Factor index and IQ scores have a mean of 100 and a

standard deviation of 15. IQ scores are intended to

estimate a child's intellectual aptitude.

Test administration alternates Performance and Verbal

subtests. The starting point for many subtests differs

depending on the child's chronological age. Items become

progressively more difficult in each subtest.

Procedure

The subjects participating in this study were assessed

by a state certified school psychologist using the third

edition of the Wechsler Intelligence Scale for Children.

The Wechsler Scale was administered as part of a battery of

tests in an appropriate environment in accordance ~'ith the

standardized procedures outlined in the WISC-III Manual.

The children assessed were referred for full diagnostic

42

evaluation. The examiner was supervised and trained in the

administration and interpretation of the WISC-III and was

employed to perform psychological evaluations. Rapport was

developed with participants prior to test administration.

Hypotheses

The following null hypotheses were investigated.

1. There will be no significant difference in the

WISC-III subtest performance of subjects referred

for clinical diagnosis from those referred for

educational diagnosis.

2. IQ scores of the educational and clinical

sample groups will not be significantly different.

3. Similarity of factor index scores will exist among

children referred in clinical and educational

settings.

4. There will be similarity in underlying factor

structure of WISC-III performance between the

educational and clinical sample groups.

5. The underlying factor structure in the current

sample will not be meaningfully different from

the factor structure listed in the WIse-III

Manual.

statistical Analysis of Data

consistent with the major hypotheses, three kinds of

statistical analyses were performed. SAS computer software

43

was used for data analysis. One-way ANOVA and t-tests for

independent samples were used to examine Hypotheses 1, 2,

and 3. These methods quantify significant statistical

differences between mean scores. The factor structure for

both groups was evaluated using the principal components and

varimax rotated methods of factor analysis to investigate

Hypotheses 4 and 5. The principal component factor method

was used to estimate the correlation matrix by finding the

eigenvalues and vectors in the matrix (Kline, 1994). The

varimax factor method is an orthogonal rotation that

maximizes the sum of variances of squared loadings in the

columns of the factor matrix (Kline, 1994). The number of

factors was predetermined at four to examine the WISC-III

factor structure. The Mazes subtest was not included in the

factor analysis because the WISC-III Manual did not suggest

that it contributed to a factor score.

The varimax factor method of orthogonal rotation was

used to adjust and interpret the differences among factors.

The varimax method verifies factors that are completely

independent of each other and polarizes factor loadings to

minimize and maximize differences. The first factor loads

the highest, the second factor accounts for variance that

was not in the first factor, and the later factors account

for those omitted in the earlier factors.

CHAPTER 4

RESULTS

44

This chapter summarizes the findings obtained by

presenting the results that emerged from the statistical

analyses. Each hypothesis is restated and evaluated against

the results.

Between Group Differences

Results Related to Hypothesis 1

The first hypothesis postulated that no similarities

would exist between children referred for clinical and

educational diagnoses in terms of their average performance

on WISC-III subtest scores. Table 4 summarizes findings

involving subtest performances of subjects in two samples.

Independent t-test comparisons confirmed that no

statistically significant differences in subtest performance

exist for subjects referred for these two types of

diagnoses. In general, the average subtest scores of

subjects in both groups were found to be below the normative

mean. The subtest means of subjects in the group referred

f~r educational diagnosis ranged from a low of 6.63 (SD =

2.94) on the Arithmetic subtest to a high of 8.5 (SD = 3.14)

on the Picture completion subtest. The average subtest

performance for the group referred for clinical diagnosis,

in contrast, ranged from a low 7.06 (SD = 3.47) on the

45

Table 4

Subtest Means, Standard Deviations, and t-Ratios for Two

Samples

Educational Clinical

(n=30) (n=30) (df=58)

M SO M SO t-ratio *p values

Information 7.56 2.83 8.93 2.58 1.95 0.06

Similari ties 7.10 2.99 8.26 3.54 1.37 0.17

Arithmetic 6.63 2.94 7.80 3.14 1.48 0.14

Vocabulary 7.16 2.67 7.96 3.31 1.02 0.30

Comprehension 7.20 3.56 8.20 3.36 1 .11 0.26

Digit Span 8.00 2.61 7.73 2.44 0.40 0.68

Picture 8.50 3.14 7.93 2.50 0.77 0.44

Completion

Coding 7.23 2.68 7.60 3.65 0.44 0.65

Picture 7.53 3.13 7.06 3.47 0.54 0.58

Arrangement

Block Design 7.76 3.58 7.80 3.73 0.03 0.97

Object 7.93 3.55 8.53 4.02 0.61 0.54

Assembly

Symbol Search 8.13 2.87 7.90 2.99 0.30 0.75

46

Picture Arrangement subtest to a high of 8.93 (SD = 2.58) on

the Information subtest. The obtained t-values (ranging

from 0.31 to 1.96) for all 12 subtest performances led to

the acceptance of Hypothesis 1, suggesting no significant

differences in WIse-III subtest performance between the two

groups of children. Equivalent statistical findings were

also obtained by analyzing data using a one-way ANOVA (see

Appendix A). F-ratios indicated no differences in

performance of subjects on verbal or non-verbal tests for

children in either group.


The second hypothesis stated that no differences in the

obtained IQs (Full Scale, Verbal, and Performance IQ) would

be found for children in the two groups. The results

related to such comparisons are presented in Table 5.

Table 5

Mean lOs, Standard Deviations, and t-Ratios for Two Samples

Educational Clinical (n=30) (n=30) (df=58)

M SD M SD t-ratio *p values

Intelligence Quotients

Full Scale IQ 84.10 13.98 87.43 15.73 0.86 0.38

Verbal IQ 83.83 14.09 90.40 14.88 1.75 0.08

Performance IQ 86.60 14.08 86.13 16.00 0.11 0.90

47

It is evident from the information contained in Table 5

that no significant differences were found between the two

sample groups in terms of the mean IQ scores. The results

obtained from one-way ANOVA (see Appendix B) provided

additional support for substantiating Hypothesis 2. The

discrepancy between the two samples on average Verbal IQ

scores appeared to be the largest, though not significantly

so. The mean Verbal IQ was 83.83 (SO = 14.09) for children

referred for educational diagnosis, while the average Verbal

IQ for the group referred for clinical diagnosis was 90.40

(SO = 14.88). The Full Scale and Performance IQ scores were

highly similar between the two groups. The Performance IQ

mean was 86.6 (SO = 14.08) for the sample tested in an

educational setting, while the average for the children

assessed in a Clinical environment was 86.13 (SO = 16.00).

The type of environment from which children were referred

evidenced no differences in average IQ scores. The

similarity between average IQ scores between the two sample

groups indicated that Hypothesis 2 cannot be rejected.


The third hypothesis stated that average factor index

scores between the two sample groups assessed at different

types of facilities would be similar. The comparison of

factor indices is depicted in Table 6.

Table 6

Factor Means, Standard Deviations. and t-Ratios for Two

Samples

Educational Clinical

(n=30) (n=30) (df=58)

48

M SO M SO t-ratio *p values

Verbal Comprehension

85.46 13.71 91.86 15.25 1.70 0.09

Perceptual Organization

88.40 15.11 87.13 15.86 0.31 0.75

Freedom from Distractibility

85.73 12.49 87.83 13.86 0.61 0.54

Processing Speed

88.20 13.57 89.30 17 .12 0.27 0.78

As indicated in Table 6, independent t-test results

concluded that there were no significant differences in

average factor index scores between the two sample groups.

commensurate findings were also noted using one-way ANOVA

(see Appendix C). The factor scores corresponding to the

subtest scores were below the normative mean for both sample

groups. Verbal Comprehension was the highest average factor

index score for the clinically referred children 91.86 (SD =

15.25), yet it was the lowest mean factor score for the

49

group of children referred for educational diagnoses 85.46

(SD = 13.71). The average index score on Factors 2, 3, and

4 was remarkably homogeneous between the two groups of

sample sUbjects. Since no significant differences were

identified in factor index scores between the two groups,

the null hypothesis is accepted.

The first three hypotheses investigated revealed that

there were no statistically significant differences between

the groups on any WISC-III variable at the .05 probability

level. Subtests, factors, and IQs, which have higher "g"

loadings, were closer to the .05 significance level.

Components that contributed less to the overall test

variance were more similar.

Comparison of Underlying Factor Structure


The fourth hypothesis suggested that groups of children

referred for diagnosis in separate environments would have

meaningfully different factor structures (see Tables 7 & 8).

As stated earlier, the performance of two groups of

subjects was factor analyzed by using a principal component

method with varimax rotation (SAS software). The

performance for each group of subjects was forced into four

factors based on the factor structure of subjects included

in the norming sample.

50

Table 7

Comparative Factor Loadings for Sample Groups

E C E C E C E C


Information 78* 85* 1 - 7 36 18 11 19

Similarities 70* 35 16 21 54* 55* -10 60*

Arithmetic 70* 73* 28 48* 12 14 21 27

Vocabulary 87* 70* 22 26 16 43 - 2 18

Comprehension 76* 63* 36 36 - 11 31 20 22

Digit Span 15 22 12 13 8 12 95* 90*

Picture 12 42 43* 40 61* 62* 18 2

Completion

Coding 7 9 85* 92* - 1 10 - 2 7

Picture 14 24 - 3 54* 84* 27 6 51*

Arrangement

Block Design 30 33 71* 20 24 75* 27 20

Object Assembly 34 12 52* 11 52* 89* - 12 16

Symbol Search 32 20 82* 88* 13 29 13 20

Educationally Referred Sample

Eigenvalues 3.29 2.64 1.89 1.14

Percent of 27.4% 22% 15.8% 9.6%

Clinically Referred Sample

Eigenvalues 2.73 2.62 2.55 1. 72

Percent of 22.8% 21.9% 21.3% 14.4%

Variance

51

Note. E = Educationally referred group, n = 30. C =

Clinically referred group, n = 30. Printed values are

multiplied by 100 and rounded to the nearest integer.

Values greater than 0.43 have been marked by an 11*." The

Mazes subtest was omitted.

This analysis related to Hypothesis 4, which compared

the similarity or difference in the factorial composition of

the WISC-III for two sample groups of sUbjects. An

examination of WISC-III factorial composition for subjects

referred for educational diagnoses demonstrated four factors

as evidenced by factor loadings. The first factor was

defined by high loadings on the Information, Similarities,

and Comprehension subtests (range of loadings = .70 to .78).

Because these loadings were produced by these three

subtests, Factor 1 can appropriately be called Verbal

Comprehension. The subtests that characterized the Verbal

Comprehension Factor produced significantly high loadings;

however, for this group, an unanticipated but equally high

factor loading was contributed by the Arithmetic subtest.

Arithmetic's significant loading on Factor 1 may be

explained by the fact that word problems, which require

adequate verbal skills, are used to solve the numerical

problems on the WISC-III.

Factor 2 is identified as Perceptual Organization and

was characterized for the educationally referred youth by

52

such marker subtests as Picture Completion, Picture

Arrangement, Block Design, and Object Assembly. Factor

loadings on these four subtests ranged from a low of .3,

produced by Picture Arrangement, to a high of .71,

contributed by Block Design. Two other subtests, Coding and

Symbol Search, also demonstrated high loadings on Factor 2.

These subtests seemed to tap different cognitive functions

as evidenced by the face value of skills required for

success on Coding and Symbol Search.

The cluster of subtests contributing to Factor 3 for

the educationally referred sample included Coding, Symbol

Search, Block Design, Object Assembly, and Picture

Completion. This factor theoretically represents Freedom

from Distractibility and significant loadings ranged from a

low of .43 on Picture Completion to a high of .85 on the

coding subtest.

The new fourth factor, Processing Speed, was derived

from an independent and very high (.95) factor loading on

the Digit Span subtest.

The sample group obtained through clinical referrals

loaded different subtests contributing to the four confirmed

factors. The subtests which comprised Factor I nearly

mirrored each other between the groups. The exception was

that the Similarities subtest did not load on the Verbal

Comprehension Factor for the clinically referred sample.

53

The subtests which created the Perceptual Organization

Factor, Factor 2, were counter-intuitive to the

nomenclature. Significant contributing subtests to Factor 2

for the clinically referred youth included Arithmetic,

Coding, Picture Arrangement, and Symbol Search. These

factor loadings ranged from a low of .48 on the Arithmetic

subtest to a high of .92 on the Coding subtest.

Freedom from Distractibility is the designated label

that the WISC-III Manual uses for Factor 3. The subtests

that substantially contributed to this factor for the

clinically referred group included Similarities (.55),

Picture Completion (.62), Block Design (.75), and Object

Assembly (.89).

An odd cluster of subtests create Factor 4 for the

clinically referred sample: Similarities, Digit Span, and

Picture Arrangement. The lowest significant factor loading

was .51 on the Picture Arrangement subtest, and the highest

was .90 on the Digit Span subtest. Factor 4 is designed to

measure Processing Speed, which logically would include

subtests requiring time limits, unlike the Similarities, and

Digit Span subtests.


The fifth hypothesis postulated that the factor

structure underlying WISC-III would be similar to the factor

structure of the entire study sample. A comparison of the

54

emerging factor structure was made using technical data

reported in the WISC-III Manual for the national norming

sample. Table 8 presents a summary of comparative factor

composition of the WISC-III for these two samples.

The composition of Factor 1 was parallel between the

total sample and norming sample except that the Arithmetic

subtest was a significant variable contributing to the

Verbal Comprehension Factor for the total sample.

The Block Design subtest loads equally in this

comparison on Factor 2: however, the other matching

significant subtests, Picture Completion and Object

Assembly, have discrepant loading values. Factors 3 and 4,

Freedom from Distractibility and Processing Speed, have no

significant variables in common between the norming group

and the total sample in the present study. Note. T = Total

sample. N = Normative Sample. The Mazes subtest was

omitted. Data for the norming sample was obtained with

permission from Wechsler Intelligence Scale for Children -

Third Edition Manual (p. 192-193) by D. Wechsler, 1991, San

Antonio: The Psychological Corporation. Copyright 1991 by

The Psychological Corporation (see Appendix D). Eigenvalues

and percentage of variance are from the total study (**),

and this information was not available for the WISC-III

norming group.

55

Table 8

WISC-III Factor structure: ComI;!arison of study and

Normative SamI;!les

T N T N T N T N

Factor Factor 2 Factor 3 Factor 4

Information 84* 72* 21 29 - 6 25 10 9

Similarities 55* 72* 49* 29 6 23 44* 9

Arithmetic 74* 42 11 27 38 73* 28 15

Vocabulary 78* 79* 33 22 18 28 17 16

Comprehension 71* 65* 23 19 27 17 17 19

Digit Span 27 26 - 1 19 14 34* 71* 18

Picture 15 38 67* 53* 21 10 33 8

Completion

Coding 11 11 14 13 94* 9 11

79*

Picture 11 33 33 37* 15 8 77* 25

Arrangement

Block Design 35 29 70* 70* 31 24 8 17

Object Assembly 27 26 86* 69* 11 11 4 14

Symbol Search 25 20 34 35 81* 19 23

56*

Eigenvalues ** 3.04 2.38 1.98 1.62

Percent of variance**

24.3% 19.9% 16.5% 13.5%

The pattern of factor composition for each sample

group, as obtained from the analysis of data, and the

WISC-III normative sample is summarized in Table 9.

Table 9

Comparison of Factor Loading Patterns for Clinical.

Educational. and Norming Samples


Information N C E

Similarities N E C E C

Vocabulary N C E

Comprehension N C E

Picture Completion N E C E

Picture Arrangement N C E C

Block Design N E C

Object Assembly N E C E

Arithmetic C E C

. Digit Span N C E

Coding C E

Symbol Search C E

N

N

N

56

57

Note. N = WISC-III norming sample, E = Educationally

referred sample, C = Clinically referred sample. The Mazes

subtest was omitted.

As illustrated in Table 9, both sample groups and the

WISC-III norming sample identified the Information,

Vocabulary, and Comprehension subtests as significant

variables which contributed to Factor 1. No other factors

were identical to the WISC-III norm group among the two

groups studied. Factors 3 and 4 were most discrepant; no

sample group clustered in a similar pattern to the WISC-III

standardization subjects. The factor loadings for the youth

in the present study did not cluster in a similar fashion to

the groupings listed in the WISC-III Technical Manual.

However, the children referred for educational diagnoses had

a closer relationship on subtests that constituted factors

than the group referred from a clinical facility.

Similarity of factor structure for the two groups of

children was empirically determined by using the statistical

method called coefficient of congruence (Harmon, 1967).

These coefficients are presented in Tables 10 -13.

58

Table 10

Coefficients of Congruence Between Matching Factors for Two

Sample Groups

Educational Setting

Factors I II III IV

I Verbal Comprehension .82

Clinical II Perceptual Organization .48

Setting III Freedom f. Distractability .90

IV Processing Speed .43

Table 11

Coefficients of Congruence Between Matching Factors in Total

Sample and Educationally Referred Groups

Educational Setting

Factors I II III IV


Total II Perceptual Organization .44

Sample III Freedom f. Distractability .92


59

Table 12


SamQle and Clinically Referred GrouQs

Clinical Setting

Factors I II III IV





Table 13


SamQle and Norming GrouQs

Norming Sample

Factors I II III IV





60

The sample groups were compared in shared factors by fou~

coefficients of congruence, and results suggested that

equivalence was obtained for Factor 1 (Verbal Comprehension)

and Factor 3 (Freedom from Distractibility). Perceptual

organization and Processing Speed factors exhibited a

differential pattern of loadings between the groups. The

minimal correlation between the sample groups on Factor 2

and 4 imply dissimilarity in factor composition.

A similar pattern of congruence is apparent in Table

11, with greater correspondence between the total sample and

the educationally referred group on Factors 1 and 3. The

relationship between factors for the group assessed in a

clinical setting as compared to the total sample resulted in

substantially higher consonance on Factors 2 and 3 and lower

but apparent correlation on Factor 1. Table 13 displays

that only Factor 1, Verbal Comprehension, was significantly

correlated between the total sample and norming group.

The congruence between WISC-III factors among the

sample groups studied was greater than the match of factors

between the total sample and the norming sample. Verbal

Comprehension is a perennial factor emerging on analyses of

the WISC-III, indicating that linguistic processing ability

is the underlying core to this assessment instrument.

CHAPTER 5

DISCUSSION

61

This study was designed to investigate the factor

structure of the 1991 version of the Wechsler Intelligence

Scale for Children, WISC-III, and to determine whether a

group of clinically referred children could be distinguished

in cognitive performance from a sample of educationally

referred children.

Contrary to the assumption that cognitive performance

would be different between groups of children based on

referral setting, the two sample groups were found to be

remarkably similar. There were small mean differences

between the groups in subtest scores, such as Arithmetic;

however, large standard deviations reduced the statistical

power. The clinical group of children had higher average

scores than the educational group on all required Verbal

subtests, reflected in higher Verbal IQ and Verbal

Comprehension Factor Index scores. This difference was

manifested in disparate diagnostic categories for the Verbal

IQ and Verbal Comprehension Factor score.

The smaller mean differences on the Performance Scale

may be explained by the lower reliability coefficients and

lower correlations of Performance subtests to the g factor

that theoretically underlies the concept of intelligence.

62

The Digit Span subtest was slightly higher for the groups of

children assessed in an educational environment. These

results implied that memory, concentration, and processing

speed may be negatively influenced for the children referred

for clinical diagnoses. Psychotropic medication or

psychomotor retardation as a symptom of depression may

contribute to diminishing the test score on this cognitive

ability (Kaufman, Grossman, & Kaufman, 1994).

Both sample groups and the WISC-III norming sample

coincided with Information, Vocabulary, and Comprehension

subtests as significant variables which contributed to

Factor 1. No other factors were matched to the WISC-III

norm group among the two groups studied. Factors 3 and 4

were most discrepant; no sample group clustered in a similar

pattern to the WISC-III standardization subjects. The

factor loadings for the youth in the present study did not

cluster in a similar fashion to the groupings listed in the

WISC-III Manual. However, the educational sample had a

closer relationship on subtests that constituted factors

than the group from a clinical setting.

Factor 1, Verbal Comprehension, for the total sample

consisted of similar but not identical subtests as reported

for this factor in the WISC-III Manual. However, the

evaluation of factor structure for each group,

independently, did not include the same variables for any

63

factor. Verbal Comprehension was the highest factor score

for the clinical group and the lowest factor score for the

educational group.

This investigation lends support to the validity of the

.WISC-III. Children who were matched on age had similar

overall cognitive performance. This study was unable to

infer specific diagnoses based on distinctive cognitive

performance among groups. The WISC-III is most beneficial

in predicting academic potential.

The conclusions of the present study should be

interpreted in light of some limitations which might have

impact on the generalizability of the obtained findings.

The primary confinement was the use of small sample groups.

A larger N in this study may have had enough power to

distinguish differences between the groups. Moreover,

without a forced four-factor pattern, differences between

the groups may be more likely to be statistically

significant. The range of children's abilities was narrowed

in the present study by evaluating only referred children.

The average Full Scale IQ in the present study was

approximately 15 points lower than the normative mean.

Similar IQ scores between groups limit the range of

variability on test profiles (Wechsler & Jaros, 1965), thus

minimizing statistical differences. Diagnostic utility is

minimal when there is homogeneity in test score patterns.

64

Psychologists must be aware that the WISC-III is likely to

produce lower IQ scores than the WISC-R and S-B IV. Lower

scores will impact special education eligibility decisions,

and caution is recommended in test comparison and

interpretation. Practitioners who depend on subtest

profiles for classifications are likely to miSdiagnose

children. The responsible psychodiagnostic ian will

demonstrate sophisticated interpretation and decision making

with WISC-III results based on further empirical

SUbstantiation.

In conclusion, it should be noted that the intellectual

performance of two groups of referred children as evidenced

by their performance on the WISC-III was found to be

remarkably similar. The similarity was also noted to a

great extent for the functions underlying test performance

for children of both groups. The obtained factor structure

was found to be similar for both study samples and for the

normative sample. However, differences in the pattern of

loadings did seem to emerge for the study as well as

normative samples. These findings should provide some

useful information for practitioners in the field.

65

APPENDIX A

SUBTEST COMPARISONS BETWEEN GROUPS

66

SUBTEST COMPARISONS BETWEEN GROUPS

df MS F *p values

Information 1 28.01 3.80 0.06

Similarities 1 20.41 1.90 0.17

Arithmetic 1 20.41 2.20 0.14

Vocabulary 1 9.60 1.06 0.30

Comprehension 1 15.0 1.25 0.26

Digit Span 1 1.06 0.17 0.68

Picture Completion 4.81 0.60 0.44

Coding 1 2.01 0.20 0.65

Picture Arrangement 1 3.26 0.30 0.58

Block Design 1 0.01 0.00 0.97

Object Assembly 1 5.40 0.37 0.54

Symbol Search 0.81 0.09 0.75

67

APPENDIX B

IQ COMPARISONS BETWEEN GROUPS

68

IQ COMPARISONS BETWEEN GROUPS

df MS F *p values

Intelligence Quotients

Full Scale IQ 1 166.66 0.75 0.38

Verbal IQ 1 646.81 3.08 0.08

Performance 10 1 3.26 0.01 0.90

69

APPENDIX C

FACTOR INDEX COMPARISONS BETWEEN GROUPS

70

FACTOR INDEX COMPARISONS BETWEEN GROUPS

df MS F *p values

Factor Indices

Verbal Comprehension 1 614.40 2.92 0.09

Perceptual Organization 1 24.06 0.10 0.75

Freedom from Distractibility 1 66.15 0.38 0.54

Processing Speed 18.15 0.08 0.78

71

APPENDIX D

PERMISSION TO REPRODUCE

o THE PSYCHOLOGICAL CORPORATION®

November 9, 1994

Ms. Dede S. Axinn Graduate Student Department of Educational Psychology The University of Arizona Tucson, Arizona 85721

Dear Ms. Axinn:

The Psychological Corporation 555 Academic Court San Antonio, Texas 78204-249H Tel 210-299-1061 Telex 5106015629 TPCSAT Fax 210-270-0327

72

Thank you for your patience while we reviewed your request to reproduce certain WISCIII material for use in your doctoral dissertation.

This letter will serve as formal authorization for the reproduction of the total sample values from Table 6.2 on page 189 of the WISC-III manual, and for reproduction of Tables 6.3, 6.4, 6.5 and 6,6 on pages 192 and 193 of the manual. Please be sure the full copyright notice from the manual appears with each table.

If you have other questions or needs, please contact us.

Sincerely,

'/ 1/ -., ; , ; /, I !., / . (, /. i /. I , t....-... < . ;. J. '. t.! ..... L. / ( __ ' • I. •. t." _ L '.j _ '_ '"

Christine Doebbler Supervisor Rights & Permissions

.·1 Sl/hsiditlry u(l/tI/"C()/lr/ Urllc(' ,-. C'UIIIIUIU\'

73

REFERENCES

Anastasi, A. (1976). PsYchological testing (4th ed.).

New York: Macmillan Publishing Co.

Atkinson, L., & Cyr, J. J. (1984). Factor analysis of

the WAIS-R: Psychiatric and standardization samples.

Journal of Consulting and Clinical Psychology, 52, 714-716.

Bannatyne, A. (1974). Diagnosis: A note on

recategorization of WISC scaled scores. Journal of Learning

Disabilities, 7, 272-274.

Barona, A. (1989). Differential effects of WISC-R

factors on special education eligibility for three ethnic

groups. Journal of Psychoeducational Assessment, 7, 31-38.

Beck, N. C., Horwitz, E., Seidenber, M., Parker, J., &

Frank, R. (1985). WAIS-R factor structure in psychiatric

and general medical patients. Journal of Consulting and

Clinical Psychology, 53, 402-505.

Bjorklund, D. F. (1989). Children's Thinking:

Developmental function and individual differences. Pacific

Grove CA: Brooks/Cole Publishing Co.

Blaha, J., & Wallbrown, F. (1984). Hierarchical

analyses of the WISC and WISC-R: Synthesis and clinical

implications. Journal of Clinical Psychology, 40, 556-571.

74

Bracken, B. A., McCallum, R. S., & Crain, R. M. (1993).

WISC-III subtest composite reliabilities and specificities:

Interpretive aids. Journal of Psychoeducational Assessment.

Advances in Psychoeducational Assessment Monograph Series.

Wechsler Intelligence Scale for Children: Third edition.

22-34.

Branden, J., & Reschly, D. (1993). The future of

assessment in public schools. Communique, 21, 9.

Carroll, J. B. (1993). What abilities are measured by

the WISC-III? Journal of Psychoeducational Assessment.



134-143.

Cattell, R. B. (1978). The scientific use of factor

analysis in behavioral and life sciences. New York:

Plenum.

Cooper, S. (1982). The clinical use and interpretation

of the Wechsler Intelligence Scale for Children - Revised.

springfield, IL: Thomas Books.

Culbert, J. P., Hamer, R., & Klinge, V. (1989). Factor

structure of the Wechsler Intelligence Scale for

Children-Revised, Peabody Picture Vocabulary Test, and

Peabody Individual Achievement Test, in a psychiatric

sample. Psychology in the Schools, 26, 331-336.

75

Dean, R. S. (1978). Distinguishing learning-disabled

and emotionally disturbed children on the WISC-R. Journal

of Consulting and Clinical Psychology, 46, 381-382.

Deitz, D. E. D., & Repp, A. C. (1989). Mental

Retardation. In T. H. Ollendick and M. Herson (Eds.),

Handbook of child psychopathology (2nd ed.). (pp. 75-91).

New York: Plenum.

Detterman, D. K. (1985). Review of the Wechsler

Intelligence Scale for Children - Revised. In J. V.

Mitchell (Ed.), The ninth mental measurement yearbook

(Vol.2, pp. 1715-1716). Lincoln, NE: Buros Institute of

Mental Measurements.

Dumont, R., & Faro, C. (1993a). A WISC-III short form

for learning disabled student. Psychology in the Schools,

30, 212-219.

Dumont, R., & Faro, C. (1993b). The WISe-III: Almost

two years old; proceeding with caution - practitioners'

concerns. communique. 21(7). 12-15.

Goh, D. S., Teslow, C. J., & Fuller, G. B. (1981). The

practice of psychological assessment among school

psychologists. Professional Psychology, 12, 696-706.

Graf, M. H., & Hinton, R. N. (1994). A 3-year

comparison study of WISC-R and WISC-III IQ scores for a

sample of special education students. Educational and

Psychological Measurement. 54, 128-133.

76

Greenblatt, E., Mattis, S., & Trad, P. V. (1991). The

ACID pattern and the Freedom from Distractibility factor in

a chil~ psychiatric population. Developmental

Neuropsychology. 7, 121-130.

Hale, R. L., & Saxe, J. E. (1983). Profile analysis of

the Wechsler Intelligence Scale for Children - Revised.

Journal of Psychoeducational Assessment. 1, 155-162.

Harman, H. H. (1967). Modern factor analysis (2nd

Ed.). Chicago: University of Chicago Press.

Harris, S. L. (1987). Infantile disorders and

childhood schizophrenia. In C. L. Frame and J. L. Matson

(Eds.), Handbook of assessment in childhood

psychopathology: Applied issues in differential diagnosis

and treatment evaluation. New York: Plenum Press.

Heim, A. W. (1975). Psychological testing. London:

Oxford university Press.

Hishinuma, E. S., & Yamakawa, R. (1993). Construct and

criterion-related validity of the WISC-III for exceptional

students and those who are "at risk". Journal of

Psychoeducational Assessment. Advances in Psychoeducational

Assessment Monograph Series.

for Children: Third edition.

Wechsler Intelligence Scale

94-104.

Hodges, K. (1982). Factor structure of the WISC-R for

a psychiatric sample. Journal of consulting and Clinical

Psychology. 50, 141-142.

77

Hutton, J. B., Dubes, R., & Muir, S. (1992).

Assessment practices of school psychologists: Ten years

later. School Psychology Review. 21, 271-284.

Kamphaus, R. W. (1993). Clinical assessment of

children's intelligence. Needham, MA: Allyn & Bacon.

Kamphaus, R. W., Benson, J., Hutchinson, s., & Platt,

L.O. (1994). Identification of factor models for the

WISC-III. Educational and Psychological Measurement, 54,

174-186.

Kamphaus, R. W., & Platt, L. O. (1992). Subtest

specificities for the WISC-III. Psychological Reports, 70,

899-902.

Kaufman, A. S. (1975). Factor analysis of the WISC-R

at eleven age levels between 6 1/2 and 16 1/2 years.


Kaufman, A. S. (1976). Verbal-Performance IQ

discrepancies on the WISC-R. Journal of Consulting and

Clinical Psychology. 44, 739-744.

Kaufman, A. S. (1979). Intelligence testing with the

WISC-R. New York: Wiley-Interscience.

Kaufman, A. S. (1993). King WISC the third assumes the

throne. Journal of School Psychology. 31, 345-354.

78

Kaufman, A. S., Grossman, I., & Kaufman, N. L. (1994).

Comparison of hospitalized depressed patients and matched

normal controls on tests that differ in their level of

cognitive complexity. Journal of Psychoeducational

Assessment. 12, 112-125.

Klausmeier, K., Mishra, S. P., & Maker, C. J. (1987).

Identification of gifted learners: A national survey of

assessment practices and training needs of school

psychologists. Gifted Child Quarterly. 31, 135-137.

Kline, P. (1991). Intelligence: The psychometric

view. London: Routledge.

Kline, P. (1994). An easy guide to factor analysis.

London: Routledge.

Larrabee, G. J., & Holroyd, R. G. (1976). Comparison

of the WISC and WISC-R using a sample of highly intelligent

children. Psychological Reports. 38, 1071-1074.

Maller, S. J. & Braden, J. P. (1993). The construct

and criterion-related validity of the WISC-III with deaf

adolescents. Journal of Psychoeducational Assessment.



105-113.

79

Matarazzo, J. D. (1972). Factoral structure of the W-B

I and WAIS. In J. D. Matarazzo (Ed.), Wechsler's

measurement and appraisal of adult intelligence (5th ed.).

New York: Oxford University Press.

McDermott, P. A., Fantuzzo J. W., & Glutting, J. J.

(1990). Just say no to subtest analysis: A critique on

Wechsler theory and practice. Journal of Psychoeducational

Assessment, 8, 290-302.

Mezzich, J. E., & Mezzich, A. C. (1987). Diagnostic

classification systems. In C. L. Frame and J. L. Matson

(Eds.), Handbook of assessment in childhood

psychopathology: Applied issues in differential diagnosis

and treatment evaluation. New York: Plenum Press.

Miller, M. M. (1980). On the attempt to find WISC-R

profiles for learning and reading disabilities (a response

to Vance, Wallbrown, & Blaha). Journal of Learning

Disabilities, 13, 338-340.

Mishra, S. P. (1984a). Recategorized WISC-R scores of

learning-disabled children from Mexican-American culture.

Journal of Clinical Psychology, 40, 1485-1488.

Mishra, S. P. (1984b). WISC-R performance patterns of

learning-disabled children from Papago culture. Journal of


80

Mishra, S. P., Ferguson, B. A., & King, P. V. (1985).

Research with the Wechsler Digit Span subtest: Implications

for assessment. School Psychology Review, 14, 37-47.

Mishra, S. P., Lord, J., & Sabers, D. L. (1989).

Cognitive processes underlying WISC-R performance of gifted

and learning disabled Navajos. Psychology in the Schools,

26, 31-36.

Naglieri, J. A. (1993). Pairwise and ipsative

comparisons of the WISC-III IQ and index scores.

Psychological Assessment, 5, 113-116.

Newby, R. F., Recht, D. R., Caldwell, J., & Schaefer,

J. (1993). Comparison of the WISC-III and WISC-R IQ changes

over a 2-year time span in a sample of children with

dyslexia. Journal of Psychoeducational Assessment.



87-93.

Piotrowski, R. J., & siegel, D. J. (1984).

Interpreting WISC-R profiles: Reliability of subtest

composites. Journal of Psychoeducational Assessment, 2,

183-190.

Post, K. R., & Mitchell, H. R. (1993). The WISC-III:

A reality check. Journal of School Psychology, 31, 541-545.

81

Prewett, P. N., & Matavich, M. A. (1994). A comparison

of referred students performance on the WISC-III and

Stanford-Binet Intelligence Scale: Fourth Edition. Journal

of psychoeducational Assessment, 12, 42-48.

Prifitera, A., & Dersh, J. (1993). Base rates of

WISC-III diagnostic subtest patterns among normal, learning

disabled, and ADHD samples. Journal of Psychoeducational

Assessment. Advances in Psychoeducational Assessment

Monograph Series. Wechsler Intelligence Scale for Children:

Third edition. 43-55.

Psychological corporation (1992). Wechsler Individual

Achievement Test Manual. San Antonio, TX: Author.

Rapoport, J. L., & Ismond, D. R. (1990). DSM-III-R

training guide for diagnosis of childhood disorders. New

York: Brunner Mazel Publishers.

Reschly, D. J. (1978). WISC-R factor structures among

Anglos, Blacks, Chicanos, and Native American Papagos.


Roid, G. H., Prifitera, A., & Weiss, L. G. (1993).

Replication of the WISC-III factor structure in an

independent sample. Journal of Psychoeducational




82

Rudel, R. G., & Denckla, M. B. (1974). Relationship of

forward and backward digit repetitions to neurological

impairment in children with learning disabilities.

Neuropsychologia, 12, 109-118.

Sattler, J. M. (1974). Assessment of children's

intelligence (Rev. ed.). Philadelphia: Saunders.

Sattler, J. M. (1982). Assessment of children's

intelligence and special abilities (2nd ed.). Boston:

Allyn & Bacon.

Sattler, J. M. (1988). Assessment of children (3rd

ed.). San Diego, CA: Jerome M. Sattler.

Sattler, J. M. (1992). Assessment of children:

WISC-III and WPPSI-R supplement. San Diego, CA: Author.

Schwean, V. L., Saklofske, D. H., Yackulic, R. A., &

Quinn, D. (1993). WISC-III performance of ADHD children.

Journal of Psychoeducational Assessment. Advances in

Psychoeducational Assessment Monograph Series. Wechsler

Intelligence Scale for Children: Third edition. 56-70.

Shavelson, R. J. (1988). statistical reasoning for the

behavioral sciences (2nd ed.). Boston: Allyn & Bacon.

Shaw, S. R., Swerdlik, & Laurent, J. (1993). Review of

the WISC-III. Journal of psychoeducational Assessment.



151-160.

83

silverstein, A. B. (1982). Pattern analysis as

simultaneous statistical inference. Journal of Clinical and

Consulting Psychology, 50, 234-240.

Silverstein, A. B. (1984). Pattern analysis: The

question of abnormality. Journal of Consulting and Clinical

Psychology, 52, 936-939.

silverstein, A. B. (1986). A literature review of

factor analytic studies of the WAIS-R. Journal of Clinical

Psychology, 42, 332-342.

spearman, C. (1927). The abilities of man. New York:

Macmillan.

Stedman, J. M., Lawlis, G. F., Cortner, R. H., &

Achterberg, G. (1978). Relationships between WISC-R

factors, Wide Range Achievem~nt Test scores, and

visual-motor maturation in children referred for a

psychological evaluation. Journal of Consulting and


Sternberg, R. J. (1993). Rocky's back again: A review

of the WISC-III. Journal of Psychoeducational Assessment.



161-164.

84

Tanner-Halverson, P., Burden, T., & Sabers, D. (1993).

WISC-III normative data for Tohono O'odham Native-American

children. Journal of Psychoeducational Assessment.



125-133.

Teeter, P. A., & Smith, P. L. (1993). WISC-III and

WJ-R: Predictive and discriminant validity for students

with severe emotional disturbance. Journal of

Psychoeducational Assessment. Advances in Psychoeducational

Assessment Monograph Series. Wechsler Intelligence Scale

for Children: Third edition. 114-124.

Thorndike, R. L., Hagen, E., & Sattler, J. M. (1986a).

stanford-Binet Intelligence Scale: Fourth Edition.

Chicago: Riverside.

Thorndike, R. L., Hagen, E., & Sattler, J. M. (1986b).

stanford-Binet Intelligence Scale: Fourth Edition,

Technical Manual. Chicago: Riverside.

Truch, S. (1993). The WISC-III companion: A guide to

interpretation and educational intervention. Austin, Texas:

PRO-ED Inc.

Wechsler, D. (1941). The measurement of adult

intelligence (2nd ed.). Baltimore: Williams & Wilkins.

Wechsler, D. (1944). The measurement of adult

intelligence (3rd ed.). Baltimore: Williams & Wilkins.

Wechsler, D. (1949). Manual for the Wechsler

Intelligence Scale for Children. New York: The

Psychological Corporation.

Wechsler, D. (1974a). Selected papers of David

Wechsler. New York: Academic Press.

85

Wechsler, D. (1974b). Manual for the Wechsler

Intelligence Scale for Children-Revised (WISC-R). New York:

The Psychological Corporation.

Wechsler, D. (1981). Manual for the Wechsler Adult

Intelligence Scale-Revised (WAIS-R). New York: The

Psychological Corporation.

Wechsler, D. (1989). Manual for the Wechsler Preschool

and Primary Scale of Intelligence- Revised (WPPSI-R). New

York: The Psychological Corporation.

Wechsler, D. (1991). Manual for the Wechsler

intelligence scale for children - Third edition. San

Antonio, TX: The Psychological corporation.

Wechsler, D., & Jaros, E. (1965). Schizophrenic

patterns on the WISC. Journal of Clinical Psychology, 21,

288-291.

86

Weiss, L. G., Prifitera, A., & Roid, G. (1993). The

WISC-III and the fairness of predicting achievement across

ethnic and gender groups. Journal of Psychoeducational




Zachary, R. A. (1990). Wechsler's intelligence scales:

Theoretical and practical considerations. Journal of

Psychoeducational Assessment, 8, 276-289.

Zimmerman, I. L., & Woo-Sam, J. M. (1985). Clinical

applications. In B. B. Wolman (Ed.), Handbook of

intelligence: Theories measurements, and applications (pp.

873-898). New York: Wiley.

Date post:	31-Mar-2021
Category:	Documents
Upload:	others
View:	0 times
Download:	0 times

Cognitive performance of children referred for clinical and … · 2020. 4. 2. · edition...

Documents