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Source files for Schneider, W. J., & Roman, Z. (2018). Fine-tuning Cross-Battery Assessment procedures: After follow-up testing, use all valid scores, cohesive or not. Journal of the Psychoeducational Assessment, 36(1), 34–54. doi: 10.1177/0734282917722861

The transition process from school to work is often challenging for young people, especially those with disabilities. In order to gather a meaningful transition, a cross battery assessment and a functional vocational evaluation are needed. In this case review study, a young adult aged 20 years 8 months, JC, had his autistic condition reviewed. Assessment was done so as to know the current status of JC’s abilities and skills and his state of readiness for vocational employment. With the results, JC could then use them to look for vocational training centers so as to develop more skills in the area of his vocational interest.

Selection, Use, and Interpretation of German Intelligence Tests for Children and Adolescents Based on CHC-theory: Update, Extension, and Critical Discussion In order to facilitate planning and interpretation of cognitive assessments for children and adolescents a CHC broad and narrow ability classification of nine widespread German tests of intelligence is presented. The Cattel-Horn-Carroll-theory of intelligence is an influential model in the field of intelligence testing. Its structure and basic premises are presented. On this basis, intelligence testing can be planned and interpreted systematically in a common theoretical framework. Practical implications and suggestions for diagnosticians (e. g. cross-battery-assessment) are pointed out. Finally, possibilities and limitations of CHC-theory in the field of intelligence testing are discussed.

This is a case review of an 8+ year-old boy diagnosed with autistic disorder when he was 3 years old. The aim of this paper is to re-examine the case to find out if there were any other comorbid conditions besides the autism that the boy had been diagnosed. In order to do it, the authors used the diagnostic model based on the hierarchy of the six building blocks of skills and abilities (Chia, 2008; 2012). This is a cross-battery assessment involving several standardized tests and checklists to be carried out. The results provide a new perspective that helps educational therapists and early interventionists to better understand and also to re-consider their treatment approach in helping the child with syndromic complex condition of autistic disorder to cope with his current learning and behavioral challenges.

We used data simulations to test whether composites consisting of cohesive subtest scores are more accurate than composites consisting of divergent subtest scores. We demonstrate that when multivariate normality holds, divergent and cohesive scores are equally accurate. Furthermore, excluding divergent scores results in biased estimates of construct scores. We show that obtaining divergent scores should prompt additional testing under some conditions. Although there are many valid reasons to exclude scores from consideration (e.g., malingering, fatigue, and misunderstood directions), no score should be removed from a composite simply because it is different from other scores in the composite.

OBJECTIVE No previous empirical study has investigated whether the LD identification decisions of proposed methods to operationalize processing strengths and weaknesses (PSW) approaches for LD identification are associated with differential treatment response. We investigated whether the identification decisions of the concordance/discordance model (C/DM; Hale & Fiorello, 2004) and Cross Battery Assessment approach (XBA method; Flanagan, Ortiz, & Alfonso, 2007) were consistent and whether they predicted intervention response beyond that accounted for by pretest performance on measures of reading. METHOD Psychoeducational assessments were administered at pretest to 203 4th graders with low reading comprehension and individual results were utilized to identify students who met LD criteria according to the C/DM and XBA methods and students who did not. Resulting group status permitted an investigation of agreement for identification methods and whether group status at pretest (LD or not LD) was associated with differential treatment response to an intensive reading intervention. RESULTS The LD identification decisions of the XBA and C/DM demonstrated poor agreement with one another (κ = -.10). Comparisons of posttest performance for students who met LD criteria and those who did not meet were largely null, with small effect sizes across all measures. CONCLUSIONS LD status, as identified through the C/DM and XBA approaches, was not associated with differential treatment response and did not contribute educationally meaningful information about how students would respond to intensive reading intervention. These results do not support the value of cognitive assessment utilized in this way as part of the LD identification process.

When education works, it works to the benefit of all. It creates productive, innovative citizens eager to contribute to a well-functioning democracy. In contrast, educational failure has lifelong c...

In Conjectures and Refutations, the philosopher of science Karl Popper (1962) stated that “the criterion of the scientific status of a theory is its falsifiability, or refutability, or testability”...

The Cross-Battery Assessment (XBA) approach to identifying a specific learning disorder (SLD) is based on the postulate that deficits in cognitive abilities in the presence of otherwise average general intelligence are causally related to academic achievement weaknesses. To examine this postulate, we conducted a classification agreement analysis using the Woodcock-Johnson III Tests of Cognitive Abilities and Achievement. We examined the broad cognitive abilities of the Cattell-Horn-Carroll theory held to be meaningfully related to basic reading, reading comprehension, mathematics calculation, and mathematics reasoning across age groups. Results of analyses of 300 participants in three age groups (6–8, 9–13, and 14–19 years) indicated that the XBA method is very reliable and accurate in detecting true negatives. Mean specificity and negative predictive value were 92% and 89% across all broad cognitive abilities and academic domains. Mean sensitivity and positive predictive values, however, were generally q...

Processing Strengths and Weaknesses (PSW) models have been proposed as a method for identifying specific learning disabilities. Three PSW models were examined for their ability to predict expert identified specific learning disabilities cases. The Dual Discrepancy/Consistency Model (DD/C; Flanagan, Ortiz, & Alfonso, 2013) as operationalized by the Cross Battery Assessment Software (X-BASS; Ortiz, Flanagan & Alfonso, 2015), the Concordance-Discordance Model (C-DM; Hale & Fiorello, 2004), and the Psychological Processing Analyzer software (PPA v3.1; Dehn, 2015b) were evaluated. The DD/C approach as represented with the X-BASS system had a 100% agreement with the expert panel in the identification of specific learning disabilities and non-specific learning disabilities cases. The C-DM model was more conservative, identifying only 45% of the specific learning disabilities cases. The PPA software was too limited to be used in the study and is not recommended for use in identifying specific learning disabilities via a PSW approach. Although more research is needed, the results of this study would suggest that the DD/C and X-BASS provide the greatest utility for a PSW approach to identifying specific learning disabilities.

The Individuals with Disabilities Education Act allows three methods of determining whether a student qualifies for special education as a student with a specific learning disability (SLD). The first and most controversial is the Discrepancy model, which requires a significant discrepancy between the student’s intellectual ability and academic achievement. The second is the Response to Intervention (RTI) model, which utilizes a process to assess a student’s response to scientific, researched-based interventions. The third method involves reviewing the student’s unique pattern of cognitive strengths and weaknesses (PSW) that result in academic deficits. The present article reviews the research regarding the strengths and weaknesses of each model. Furthermore, due to the recent emergence of PSW models, this article concludes with the authors’ recommendations for further research prior to implementation of the PSW approach.

This chapter describes the purpose of cross-battery assessment, i.e., to provide psychological assessment specialists/examiners with an overall cognitive assessment strategy. More specifically, it is designed to make examiners aware of the subconstructs of intelligence, as defined by the Cattell–Horn–Carroll Model of intelligence, and to make them aware of how these constructs can be assessed, using the best available operationalizations (of the constructs). Cross-battery assessment principles can be used by examiners to determine cognitive strengths and weaknesses, and is generally considered to provide the steps necessary to complete a very comprehensive evaluation of cognitive abilities. I have adapted the guidelines and principles from McGrew and Flanagan (1998) and Flanagan et al. (2013) for those examiners who engage in nonverbal assessment of cognitive abilities and intelligence. In addition, I provide a listing of the best nonverbal assessment instruments (Appendix 1) and a set of worksheets to guide interpretation of scores obtained from nonverbal cross-battery assessment (Appendix 2). Finally, I provide a case for illustrative purposes in Appendix 3. As is apparent from reading the case, the basic principles and strategies are the same for both verbal and nonverbal assessment, but the number and quality of instruments available for nonverbal assessment are less than for verbal assessment.

The Cattell-Horn-Carroll (CHC) cross-battery approach to assessing cognitive abilities has been introduced to the field recently as an alternative to traditional assessment instruments and techniques (Flanagan, McGrew, & Ortiz, 2000; McGrew & Flanagan, 1998). This theory-based method of assessment was developed to provide a more valid and defensible way of deriving meaning from test scores than that provided by the traditional (and largely atheoretical) Wechsler Scale approach. The present study is the first to investigate the validity of the cross-battery approach using a sample of elementary school children (N= 166) who were administered the Wechsler Intelligence Scale for Children-Revised (WISC-R; Wechsler, 1974) and Woodcock-Johnson Psycho-Educational Battery-Revised (WJ-R; Woodcock & Johnson, 1989). Structural Equation Modeling was used to examine whether (a) Wechsler-based CHC cross-battery assessment explained more variance in reading achievement than a traditional Wechsler model, and (b) whether the Wechsler-based CHC cross-battery model provided a more accurate description of the general and specific abilities on general and specific reading achievement than the traditional Wechsler model, as predicted in the extant ^/specific abilities literature. Findings showed that the g factor underlying the Wechsler-based CHC cross-battery model accounted for substantially more variance in reading achievement (25%) than the g factor underlying the atheoretical Verbal Comprehension-Perceptual Organization-Freedom From Distractibility (VC-PO-FFD) Wechsler model. In addition, findings demonstrated that when assessments are organized around the strong CHC theoretical model, specific cognitive abilities, including auditory processing (Ga), crystallized intelligence (Gc), and processing speed (Gs) explained a significant portion of variance in reading achievement beyond that accounted for by g. These

Few empirical investigations have evaluated learning disabilities (LD) identification methods based on a pattern of cognitive strengths and weaknesses (PSW). This study investigated the reliability and validity of two proposed PSW methods: the concordance/discordance method (C/DM) and cross battery assessment (XBA) method. Cognitive assessment data for 139 adolescents demonstrating inadequate response to intervention was utilized to empirically classify participants as meeting or not meeting PSW LD identification criteria using the two approaches, permitting an analysis of: (a) LD identification rates, (b) agreement between methods, and (c) external validity. LD identification rates varied between the 2 methods depending upon the cut point for low achievement, with low agreement for LD identification decisions. Comparisons of groups that met and did not meet LD identification criteria on external academic variables were largely null, raising questions of external validity. This study found low agreement and little evidence of validity for LD identification decisions based on PSW methods. An alternative may be to use multiple measures of academic achievement to guide intervention.

The Cattell-Horn-Carroll (CHC) Cross-Battery approach, originally known as the Gf-Gc Cross-Battery model of assessment, has been defined as “a time efficient method of intellectual assessment that allows practitioners to measure validly a wider range (or a more in-depth but selective range) of cognitive abilities than that represented by any one intelligence battery in a way consistent with contemporary psychometric theory and research on the structure of intelligence” (McGrew & Flanagan, 1998, p. 357). The CHC Cross-Battery approach provides at least two unique advantages: (a) data gathered both within and across test batteries can be interpreted theoretically and empirically within meaningful patterns; and (b) cognitive test data lead to examination of empirically validated links between specific cognitive abilities and specific academic areas (Flanagan & Ortiz, 2001). The approach provides practitioners with a classification system of cognitive abilities; existing cognitive tests can be evaluated according to the model, that is, subcomponents/subtests can be described based on their ability to assess cognitive abilities within the CHC model.