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Joseph A Buckhalt - One of the best experts on this subject based on the ideXlab platform.
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respiratory sinus arrhythmia and cognitive functioning in children
Developmental Psychobiology, 2009Co-Authors: Lori Staton, Mona Elsheikh, Joseph A BuckhaltAbstract:We examined associations between children's cognitive performance and both basal respiratory sinus arrhythmia (RSA) and RSA regulation to a reaction time task. Cognitive performance was examined in the lab via standardized tests of cognitive functioning (Woodcock–Johnson III) and a reaction time task. Results suggest that a higher level of basal RSA is predictive of better performance on WJ III scales examining fluid intelligence (e.g., working memory, cognitive efficiency). RSA reactivity was not significantly related to cognitive performance. Results build on and extend the literature by demonstrating that, in typically developing elementary school age children, RSA is related to well-standardized measures of cognitive performance even after controlling for potential confounds. © 2008 Wiley Periodicals, Inc. Dev Psychobiol 51: 249–258, 2009
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children s sleep and cognitive functioning race and socioeconomic status as moderators of effects
Child Development, 2007Co-Authors: Joseph A Buckhalt, Mona Elsheikh, Peggy S KellerAbstract:Race and socioeconomic status (SES) moderated the link between children's sleep and cognitive functioning. One hundred and sixty-six 8- to 9-year-old African and European American children varying in SES participated. Sleep measures were actigraphy, sleep diaries, and self-report; cognitive measures were from the Woodcock–Johnson III and reaction time tasks. Children had similar performance when sleep was more optimal, but after controlling for SES, African American children had lower performance with sleep disruptions. Children from lower and higher SES had similar performance with better sleep quality and less variability in sleep schedules, but when sleep was more disrupted, higher SES children had better performance. Examination of environmental variables associated with race and SES that may underlie these effects may lead to directions for interventions to improve cognitive performance.
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An Investigation of Gf-Gc Theory in the Older Adult Population: Joint Factor Analysis of the Woodcock-Johnson–Revised and the Detroit Test of Learning Aptitude–Adult
Psychological Reports, 2001Co-Authors: Joseph A Buckhalt, Ron L. Mcghee, David J. EhrlerAbstract:Researchers and clinicians are increasingly interested in the structure of intelligence among older adults. A joint factor analysis was conducted for 27 subtests of the Woodcock-Johnson Psycho-Educational Battery–Revised and the Detroit Tests of Learning Aptitude–Adult for a sample of 50 persons ranging in age from 55 to 84 years ( M = 65.16 yr.). The results provide evidence for the latent factors specified by Gf-Gc theory in older adults, indicate which Gf-Gc factors are measured by subtests of the two batteries, and illustrate the necessity of cross-battery assessment to identify the full complement of Gf-Gc factors.
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An investigation of Gf-Gc theory in the older adult population: joint factor analysis of the Woodcock-Johnson-Revised and the Detroit Test of Learning Aptitude-Adult.
Psychological reports, 2001Co-Authors: Joseph A Buckhalt, Ron L. Mcghee, David J. EhrlerAbstract:Researchers and clinicians are increasingly interested in the structure of intelligence among older adults. A joint factor analysis was conducted for 27 subtests of the Woodcock-Johnson Psycho-Educational Battery-Revised and the Detroit Tests of Learning Aptitude-Adult for a sample of 50 persons ranging in age from 55 to 84 years (M=65.16 yr.). The results provide evidence for the latent factors speci fied by Gf-Gc theory in older adults, indicate which Gf-Gc factors are measured by subtests of the two batteries, and illustrate the necessity of cross-battery assessment to identify the full complement of Gf-Gc factors.
Kevin S. Mcgrew - One of the best experts on this subject based on the ideXlab platform.
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General and Specific Effects on Cattell-Horn-Carroll Broad Ability Composites: Analysis of the Woodcock-Johnson III Normative Update Cattell-Horn-Carroll Factor Clusters across Development.
School Psychology Review, 2009Co-Authors: Randy G. Floyd, Kevin S. Mcgrew, Amberly Barry, Fawziya A. Rafael, Joshua RogersAbstract:Abstract. Many school psychologists focus their interpretation on composite scores from intelligence test batteries designed to measure the broad abilities from the Cattell-Horn-Carroll theory. The purpose of this study was to investigate the general factor loadings and specificity of the broad ability composite scores from one such intelligence test battery, the Woodcock-Johnson HI Tests of Cognitive Abilities Normative Update (Woodcock, McGrew, Schrank, & Mather, 2007). Results from samples beginning at age 4 and continuing through age 60 indicate that Comprehension-Knowledge, Long-Term Retrieval, and Fluid Reasoning appear to be primarily measures of the general factor at many ages. In contrast, Visual-Spatial Thinking, Auditory Processing, and Processing Speed appear to be primarily measures of specific abilities at most ages. We offer suggestions for considering both the general factor and specific abilities when interpreting Cattell-Horn-Carroll broad ability composite scores. ********** School psychologists have been inundated this decade with intelligence test batteries that provide a variety of composites representing specific cognitive abilities. The majority of the specific cognitive abilities targeted by these contemporary test batteries are grounded in design blueprints based on the Cattell-Horn-Carroll (CHC) theory (1) (see Alfonso, Flanagan, & Radwan, 2005). The composites from these batteries are most often designed to measure the broad abilities of CHC theory, such as Crystallized Intelligence and Fluid Intelligence. In addition to intelligence test batteries based on the CHC design blueprint, interpretive approaches guiding users to form composites within and across batteries based on CHC theory have proliferated (e.g., Flanagan, Ortiz, & Alfonso, 2007; McGrew & Flanagan, 1998). Because broad ability composite scores typically possess substantial validity evidence and have overcome reliability limitations inherent in the interpretation of subtest scores (McGrew, 1997; Watkins, Glutting, & Youngstrom, 2005), there has also been increased research focused on their interpretation within score profiles (e.g., Bergeron & Floyd, 2006; Floyd, Bergeron, & Alfonso, 2006; Proctor, Floyd, & Shaver, 2005). Despite this increased prevalence of test batteries, interpretive approaches, and research employing composite scores based on CHC theory, some important measurement properties of these broad ability composite scores remain unstudied--the effects of general and specific cognitive abilities. The goal of this article is to produce the estimates of these effects on the broad ability composite scores from the first intelligence test battery based on CHC theory, the Woodcock-Johnson III Tests of Cognitive Abilities (WJIII COG; Woodcock, McGrew, & Mather, 2001). General and Specific Abilities Mental ability as a general, unitary trait was first postulated by Spearman (1904) based on his observation that all mental test scores were positively intercorrelated. Spearman supported this postulation with research using factor analysis. This method led him to discover the general factor (Spearman, 1927) underlying the positive manifold across mental ability test scores. Since the time of Spearman, hundreds of studies have demonstrated that the general factor accounts for approximately 25% to 50% of the variance shared by such tests--typically the largest percentage of any factor. In addition, another large body of research has demonstrated that scores representing the general factor (e.g., IQs) are strong predictors of representations of personal competence, such as academic success and job performance (see Jensen, 1998; Schmidt, 2002). Despite extensive evidence for the general factor and its predictive properties, a number of challenges to its primacy has been levied. Some scholars have argued that largely independent, specific cognitive abilities better account for the relations between and among mental test scores. …
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Effects of general and broad cognitive abilities on mathematics achievement.
School Psychology Quarterly, 2008Co-Authors: Gordon E. Taub, Randy G. Floyd, Timothy Z. Keith, Kevin S. McgrewAbstract:This study investigated the direct and indirect effects of general intelligence and 7 broad cognitive abilities on mathematics achievement. Structural equation modeling was used to investigate the simultaneous effects of both general and broad cognitive abilities on students’ mathematics achievement. A hierarchical model of intelligence derived from the Cattell–Horn–Carroll (CHC) taxonomy of intelligence was used for all analyses. The participants consisted of 4 age-differentiated subsamples (ranging from ages 5 to 19) from the standardization sample of the Woodcock–Johnson III (WJ III; Woodcock, McGrew, & Mather, 2001). Data from each of the 4 age-differentiated subsamples were divided into 2 data sets. At each age level, one data set was used for model testing and modification, and a second data set was used for model validation. The following CHC broad cognitive ability factors demonstrated statistically significant direct effects on the mathematics achievement variables: Fluid Reasoning, Crystallized Intelligence, and Processing Speed. In contrast, across all age levels, the general intelligence factor demonstrated indirect effects on the mathematics achievement variable.
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Uniqueness and General Factor Characteristics of the Woodcock-Johnson Tests of Cognitive Ability-Revised
Journal of School Psychology, 1995Co-Authors: Kevin S. Mcgrew, Suzanne R. MurphyAbstract:Abstract When new or revised intelligence batteries are published, it is important to know the general factor loading and uniqueness information of the individual tests prior to using them for clinical interpretation. This study investigated the general factor and uniqueness characteristics of the individual tests of the Woodcock-Johnson Test of Cognitive Ability-Revised (WJTCA-R), a revised and expanded version of the 1977 Woodcock-Johnson Test of Cognitive Ability. The subjects were drawn from the nationally representative WJTCA-R standardization sample and were organized into 18 different age categories. Only 2 (Incomplete Words and Visual Closure) of the 19 WJTCA-R tests examined had low general factor loadings. The remaining 17 tests had medium or high general factor loadings. Only 2 (Cross Out and Listening Comprehension) of the 19 WJTCA-R tests had low uniqueness. All other tests had medium or high uniqueness. The implications for clinical interpretation are discussed.
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Use of the Woodcock-Johnson-Revised Writing Tests with Students with Learning Disabilities
Journal of Psychoeducational Assessment, 1991Co-Authors: Nancy Mather, Susan A. Vogel, Ruth B. Spodak, Kevin S. McgrewAbstract:This study investigated the performance of 47 sixth-through eighth-grade students with learning disabilities on the Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R) writing tests (Woodcock &Johnson, 1989). The purposes were to investigate the construct and concurrent validity of these new tests. The students' WJ-R writing cluster scores were compared to those of a random sample of 47 students selected from the WJ-R standardization group. In addition, interrater reliability for the WJ-R Writing Samples tests was investigated, and the correlations among the WJ-R writing clusters and tests and several other writing tests were examined. The results supported findings of previous studies; students with learning disabilities have significantly more difficulty with basic writing skills than do their non-learning-disabled peers. The intercorrelations and interrater reliability study provide further support for the validity of the WJ-R writing tests.
Randy G. Floyd - One of the best experts on this subject based on the ideXlab platform.
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Use of the Woodcock–Johnson IV Tests of Cognitive Abilities in the Diagnosis of Intellectual Disability
WJ IV Clinical Use and Interpretation, 2016Co-Authors: Randy G. Floyd, Isaac L. Woods, Leah J. Singh, Haley K. HawkinsAbstract:Abstract This chapter begins with an overview of the eligibility and diagnostic criteria for intellectual disability (ID), continues to discuss test and score properties that are important when assessing for ID, follows with an evaluation of the Woodcock–Johnson IV (WJ IV) Tests of Cognitive Abilities (COG) in terms of it addressing these properties, and ends with a case study. Evidence supporting the use and interpretation of the General Intellectual Ability and Gf–Gc Composite from the WJ IV COG is highlighted and evaluated, and applications of these scores to practice are presented.
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General and Specific Effects on Cattell-Horn-Carroll Broad Ability Composites: Analysis of the Woodcock-Johnson III Normative Update Cattell-Horn-Carroll Factor Clusters across Development.
School Psychology Review, 2009Co-Authors: Randy G. Floyd, Kevin S. Mcgrew, Amberly Barry, Fawziya A. Rafael, Joshua RogersAbstract:Abstract. Many school psychologists focus their interpretation on composite scores from intelligence test batteries designed to measure the broad abilities from the Cattell-Horn-Carroll theory. The purpose of this study was to investigate the general factor loadings and specificity of the broad ability composite scores from one such intelligence test battery, the Woodcock-Johnson HI Tests of Cognitive Abilities Normative Update (Woodcock, McGrew, Schrank, & Mather, 2007). Results from samples beginning at age 4 and continuing through age 60 indicate that Comprehension-Knowledge, Long-Term Retrieval, and Fluid Reasoning appear to be primarily measures of the general factor at many ages. In contrast, Visual-Spatial Thinking, Auditory Processing, and Processing Speed appear to be primarily measures of specific abilities at most ages. We offer suggestions for considering both the general factor and specific abilities when interpreting Cattell-Horn-Carroll broad ability composite scores. ********** School psychologists have been inundated this decade with intelligence test batteries that provide a variety of composites representing specific cognitive abilities. The majority of the specific cognitive abilities targeted by these contemporary test batteries are grounded in design blueprints based on the Cattell-Horn-Carroll (CHC) theory (1) (see Alfonso, Flanagan, & Radwan, 2005). The composites from these batteries are most often designed to measure the broad abilities of CHC theory, such as Crystallized Intelligence and Fluid Intelligence. In addition to intelligence test batteries based on the CHC design blueprint, interpretive approaches guiding users to form composites within and across batteries based on CHC theory have proliferated (e.g., Flanagan, Ortiz, & Alfonso, 2007; McGrew & Flanagan, 1998). Because broad ability composite scores typically possess substantial validity evidence and have overcome reliability limitations inherent in the interpretation of subtest scores (McGrew, 1997; Watkins, Glutting, & Youngstrom, 2005), there has also been increased research focused on their interpretation within score profiles (e.g., Bergeron & Floyd, 2006; Floyd, Bergeron, & Alfonso, 2006; Proctor, Floyd, & Shaver, 2005). Despite this increased prevalence of test batteries, interpretive approaches, and research employing composite scores based on CHC theory, some important measurement properties of these broad ability composite scores remain unstudied--the effects of general and specific cognitive abilities. The goal of this article is to produce the estimates of these effects on the broad ability composite scores from the first intelligence test battery based on CHC theory, the Woodcock-Johnson III Tests of Cognitive Abilities (WJIII COG; Woodcock, McGrew, & Mather, 2001). General and Specific Abilities Mental ability as a general, unitary trait was first postulated by Spearman (1904) based on his observation that all mental test scores were positively intercorrelated. Spearman supported this postulation with research using factor analysis. This method led him to discover the general factor (Spearman, 1927) underlying the positive manifold across mental ability test scores. Since the time of Spearman, hundreds of studies have demonstrated that the general factor accounts for approximately 25% to 50% of the variance shared by such tests--typically the largest percentage of any factor. In addition, another large body of research has demonstrated that scores representing the general factor (e.g., IQs) are strong predictors of representations of personal competence, such as academic success and job performance (see Jensen, 1998; Schmidt, 2002). Despite extensive evidence for the general factor and its predictive properties, a number of challenges to its primacy has been levied. Some scholars have argued that largely independent, specific cognitive abilities better account for the relations between and among mental test scores. …
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Effects of general and broad cognitive abilities on mathematics achievement.
School Psychology Quarterly, 2008Co-Authors: Gordon E. Taub, Randy G. Floyd, Timothy Z. Keith, Kevin S. McgrewAbstract:This study investigated the direct and indirect effects of general intelligence and 7 broad cognitive abilities on mathematics achievement. Structural equation modeling was used to investigate the simultaneous effects of both general and broad cognitive abilities on students’ mathematics achievement. A hierarchical model of intelligence derived from the Cattell–Horn–Carroll (CHC) taxonomy of intelligence was used for all analyses. The participants consisted of 4 age-differentiated subsamples (ranging from ages 5 to 19) from the standardization sample of the Woodcock–Johnson III (WJ III; Woodcock, McGrew, & Mather, 2001). Data from each of the 4 age-differentiated subsamples were divided into 2 data sets. At each age level, one data set was used for model testing and modification, and a second data set was used for model validation. The following CHC broad cognitive ability factors demonstrated statistically significant direct effects on the mathematics achievement variables: Fluid Reasoning, Crystallized Intelligence, and Processing Speed. In contrast, across all age levels, the general intelligence factor demonstrated indirect effects on the mathematics achievement variable.
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Cattell–Horn–Carroll cognitive ability profiles of poor comprehenders
Reading and Writing, 2006Co-Authors: Randy G. Floyd, Renee Bergeron, Vincent C. AlfonsoAbstract:This study examines cognitive ability profiles of children with specific age-based normative weaknesses in reading comprehension and compares those profiles to the profiles of (a) children with at least average achievement in reading comprehension, reading decoding skills, and mathematics and (b) children with low achievement across the 3 achievement areas. When compared across 9 cognitive ability composite scores derived from Cattell–Horn–Carroll theory and measured by the Woodcock–Johnson III [Woodcock, McGrew, & Mather (2001). Woodcock–Johnson . Itasca, IL: Riverside], groups differed in overall level of performance. When individual abilities were considered, the poor comprehenders scored significantly lower than the average achievement group on all nine composite scores and significantly lower than the normative population on all composite scores except Processing Speed and Long-Term Retrieval. In contrast, the poor comprehenders also scored significantly higher than the low achievement group on all composite scores except for Visual–Spatial Thinking and Phonemic Awareness. Although the poor comprehenders as a group scored lowest on composite scores measuring language- and knowledge-based abilities, review of the profiles of individual poor comprehenders revealed no consistent pattern of performance across cognitive ability composite scores.
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Using the Woodcock-Johnson III Tests of Cognitive Abilities with Students with Attention Deficit/Hyperactivity Disorder
WJ III Clinical Use and Interpretation, 2003Co-Authors: Laurie Ford, Randy G. Floyd, Timothy Z. Keith, Cheryl Fields, Fredrick A. SchrankAbstract:Publisher Summary This chapter discusses cognitive abilities with students with attention deficit (AD) and hyperactivity disorder (HD) using the Woodcock–Johnson III tests. This chapter includes four parts. The first part includes a brief summary of the most frequently used diagnostic criteria and approaches to diagnosing AD/HD, and suggests use of a behavioral–cognitive model that includes assessment of behavioral characteristics as well as certain cognitive functions that may be sensitive to the condition, as suggested by prior research. The second part contains a description of extant research about use of the prior and current editions of the Woodcock–Johnson with individuals who have AD/HD. The third and major part of this chapter presents the results of a study of utility of the WJ III tests that comprise the Executive Processes, Working Memory, and Broad Attention clusters and selected checklists from Report Writer in prediction of AD/HD. The fourth and final part of this chapter includes a discussion of the clinical applications of the WJ III and Report Writer for assessment of individuals who may have AD/HD. Moreover, the WJ III COG may be useful for describing the executive processing characteristics of an individual who has AD/HD, such as any concomitant limitations in working memory capacity and/or inattention to cognitive task demands. This type of cognitive processing information can be used to support a diagnosis of AD/HD and may assist in identifying needed services and interventions. Finally, a case illustration completes the section.
David J. Ehrler - One of the best experts on this subject based on the ideXlab platform.
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An Investigation of Gf-Gc Theory in the Older Adult Population: Joint Factor Analysis of the Woodcock-Johnson–Revised and the Detroit Test of Learning Aptitude–Adult
Psychological Reports, 2001Co-Authors: Joseph A Buckhalt, Ron L. Mcghee, David J. EhrlerAbstract:Researchers and clinicians are increasingly interested in the structure of intelligence among older adults. A joint factor analysis was conducted for 27 subtests of the Woodcock-Johnson Psycho-Educational Battery–Revised and the Detroit Tests of Learning Aptitude–Adult for a sample of 50 persons ranging in age from 55 to 84 years ( M = 65.16 yr.). The results provide evidence for the latent factors specified by Gf-Gc theory in older adults, indicate which Gf-Gc factors are measured by subtests of the two batteries, and illustrate the necessity of cross-battery assessment to identify the full complement of Gf-Gc factors.
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An investigation of Gf-Gc theory in the older adult population: joint factor analysis of the Woodcock-Johnson-Revised and the Detroit Test of Learning Aptitude-Adult.
Psychological reports, 2001Co-Authors: Joseph A Buckhalt, Ron L. Mcghee, David J. EhrlerAbstract:Researchers and clinicians are increasingly interested in the structure of intelligence among older adults. A joint factor analysis was conducted for 27 subtests of the Woodcock-Johnson Psycho-Educational Battery-Revised and the Detroit Tests of Learning Aptitude-Adult for a sample of 50 persons ranging in age from 55 to 84 years (M=65.16 yr.). The results provide evidence for the latent factors speci fied by Gf-Gc theory in older adults, indicate which Gf-Gc factors are measured by subtests of the two batteries, and illustrate the necessity of cross-battery assessment to identify the full complement of Gf-Gc factors.
Gordon E. Taub - One of the best experts on this subject based on the ideXlab platform.
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Invariance of Woodcock-Johnson III scores for students with learning disorders and students without learning disorders.
School psychology quarterly : the official journal of the Division of School Psychology American Psychological Association, 2013Co-Authors: Nicholas F. Benson, Gordon E. TaubAbstract:The purpose of this study was to test the invariance of scores derived from the Woodcock-Johnson III Tests of Cognitive Ability (WJ III COG) and Woodcock-Johnson III Tests of Academic Achievement (WJ III ACH) across a group of students diagnosed with learning disorders (n = 994) and a matched sample of students without known clinical diagnoses (n = 994). This study focused on scores reflecting broad cognitive abilities and areas of academic achievement in which children may demonstrate learning disabilities. Results of this study support the conclusion that the WJ III COG and WJ III ACH measure similar constructs for students with learning disabilities and students without learning disabilities. However, large and pervasive between-groups differences were found with regard to intercepts. Intercepts can be defined as predicted group means for individual tests, in which predicted group means are based on the factor loadings of these tests on the latent variable they are intended to measure. As many intercepts are not equivalent, it is possible that observed scores may not accurately reflect differences in the construct of interest when testing children with learning disabilities. However, tests displaying the largest intercept differences also displayed the largest group differences in observed scores, providing some support for the conclusion that these differences reflect construct-relevant between-group differences. Implications of this research are discussed.
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Effects of general and broad cognitive abilities on mathematics achievement.
School Psychology Quarterly, 2008Co-Authors: Gordon E. Taub, Randy G. Floyd, Timothy Z. Keith, Kevin S. McgrewAbstract:This study investigated the direct and indirect effects of general intelligence and 7 broad cognitive abilities on mathematics achievement. Structural equation modeling was used to investigate the simultaneous effects of both general and broad cognitive abilities on students’ mathematics achievement. A hierarchical model of intelligence derived from the Cattell–Horn–Carroll (CHC) taxonomy of intelligence was used for all analyses. The participants consisted of 4 age-differentiated subsamples (ranging from ages 5 to 19) from the standardization sample of the Woodcock–Johnson III (WJ III; Woodcock, McGrew, & Mather, 2001). Data from each of the 4 age-differentiated subsamples were divided into 2 data sets. At each age level, one data set was used for model testing and modification, and a second data set was used for model validation. The following CHC broad cognitive ability factors demonstrated statistically significant direct effects on the mathematics achievement variables: Fluid Reasoning, Crystallized Intelligence, and Processing Speed. In contrast, across all age levels, the general intelligence factor demonstrated indirect effects on the mathematics achievement variable.
