The Development and Applied Utility of a Normative Aptitude–achievement Taxonomy for the Woodcock-Johnson Psycho-Educational Battery-Revised

Konold, Timothy R.; Glutting, Joseph J.; McDermott, Paul A.

doi:10.1177/002246699703100204

Cited by 18 publications

(10 citation statements)

References 24 publications

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“…Means and standard deviations for the six tests comprising the constructs of phonological awareness, oral comprehension, and reading aptitude used to identify normative profiles through cluster analysis are presented in Table 1. The clustering strategy we adopted was similar to the one used elsewhere for identifying normative profiles (Glutting & McDermott, 1990;Glutting et al, 1997;Konold et al, 1997;Konold, Glutting, McDermott, Kush, & Watkins, 1999;McDermott, Glutting, Jones, & Noonan, 1989), as described in McDermott (1998). This procedure involved three steps.…”

Section: Data Analyses and Resultsmentioning

confidence: 99%

A multivariate model of early reading acquisition

Konold

Juel

McKinnon

et al. 2003

Applied Psycholinguistics

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How similar are the cognitive and linguistic profiles of those children who easily learn to read? How similar are the profiles of those children who have difficulty learning to read? Do the profiles of successful and less successful readers vary among children 5-10 years of age? These were the questions that guided this study. Six core profiles were identified on four fluid reasoning to comprehension knowledge constructs previously found to be both theoretically and empirically linked to children's reading acquisition: auditory processing, crystallized ability, processing speed, and shortterm memory. Cluster analysis was used to develop this taxonomy and the six-cluster solution was supported through cross-validation. The internal and external validity of the resulting profiles was favorable, suggesting homogeneous within-cluster membership and clear separation among the six core profiles. A summary of the defining characteristics for each profile is provided. The performance of children comprising different profiles was investigated on four external reading outcomes. These comparisons were conducted for each of the six age groups comprising the sample (i.e., 5-10 years) to assess whether the importance of certain score configurations varied as a function of the reading tasks required of children learning to read and those who are already readers. Results indicated that certain profiles were associated with greater success on external measures of reading achievement than other profiles. Trends across ages and differences among age groups are described.

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Section: Data Analyses and Resultsmentioning

confidence: 99%

A multivariate model of early reading acquisition

Konold

Juel

McKinnon

et al. 2003

Applied Psycholinguistics

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“…On the other hand, the PAMS analysis uses a continuous representation of individual differences. In the cluster approach, a researcher may add a continuous measure of profile match to index the degree to which each person's profile matches a pattern identified by the clustering (e.g., Konold, Glutting, & McDermott, 1997;Konold et al, 1999), but a cluster is fundamentally a categorical representation of individual differences. The PAMS model itself includes measures of profile match that could be used by clinicians and researchers.…”

Section: Discussionmentioning

confidence: 99%

Estimating Cognitive Profiles Using Profile Analysis via Multidimensional Scaling (PAMS)

Kim¹,

Frisby²,

Davison³

2004

Multivariate Behavioral Research

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Two of the most popular methods of profile analysis, cluster analysis and modal profile analysis, have limitations. First, neither technique is adequate when the sample size is large. Second, neither method will necessarily provide profile information in terms of both level and pattern. A new method of profile analysis, called Profile Analysis via Multidimensional Scaling (PAMS; Davison, 1996), is introduced to meet the challenge. PAMS extends the use of simple multidimensional scaling methods to identify latent profiles in a multi-test battery. Application of PAMS to profile analysis is described. The PAMS model is then used to identify latent profiles from a subgroup (N = 357) within the sample of the Woodcock-Johnson Psychoeducational Battery-Revised (WJ-R; McGrew, Werder, & Woodcock, 1991; Woodcock & Johnson, 1989), followed by a discussion of procedures for interpreting participants' observed score profiles from the latent PAMS profiles. Finally, advantages and limitations of the PAMS technique are discussed.

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“…The factor scores were standardized ( M = 0, SD = 1) within the total sample prior to analysis. The clustering strategy we adopted was similar to one used elsewhere for identifying normative profiles (Glutting & McDermott, 1990; Glutting, McDermott, & Konold, 1997; Konold, Glutting, & McDermott, 1997), as described in McDermott (1998). This procedure involved three steps.…”

Section: Methodsmentioning

confidence: 99%

Subgroups of adult basic education learners with different profiles of reading skills

et al. 2010

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The purpose of this study was to identify subgroups of adult basic education (ABE) learners with different profiles of skills in the core reading components of decoding, word recognition, spelling, fluency, and comprehension. The analysis uses factor scores of those 5 reading components from on a prior investigation of the reliability and construct validity of measures of reading component skills (MacArthur, Konold, Glutting, & Alamprese, 2010). In that investigation, confirmatory factor analysis found that a model with those 5 factors fit the data best and fit equally well for native and non-native English speakers. The study included 486 students, 334 born or educated in the United States (native) and 152 not born nor educated in the US (non-native) but who spoke English well enough to participate in English reading classes. The cluster analysis found an 8-cluster solution with good internal cohesion, external isolation, and replicability across subsamples. Of the 8 subgroups, 4 had relatively flat profiles (range of mean scores across factors < 0.5 SD), 2 had higher comprehension than decoding, and 2 had higher decoding than comprehension. Profiles were consistent with expectations regarding demographic factors. Non-native speakers were overrepresented in subgroups with relatively higher decoding and underrepresented in subgroups with relatively higher comprehension. Adults with self-reported learning disabilities were overrepresented in the lowest performing subgroup. Older adults and men were overrepresented in subgroups with lower performance. The study adds to the limited research on the reading skills of ABE learners and, from the perspective of practice, supports the importance of assessing component skills to plan instruction.

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The Development and Applied Utility of a Normative Aptitude–achievement Taxonomy for the Woodcock-Johnson Psycho-Educational Battery-Revised

Cited by 18 publications

References 24 publications

A multivariate model of early reading acquisition

A multivariate model of early reading acquisition

Estimating Cognitive Profiles Using Profile Analysis via Multidimensional Scaling (PAMS)

Subgroups of adult basic education learners with different profiles of reading skills

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