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Monday, July 26, 2010
iPost: Special JID issue on Gv (visual-spatial abilities)
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Research bytes 7-26-1-: Lots of good intelligence, cognitive, neuro, Big 5, genetic, working memory research stuff
Usual offer -- would you like to read the actual article...in exchange for a brief guest blog post at IQ's Corner? Contact blogmaster (iap@earthlink.net) if interested.
Ferrer, E., & McArdle, J. J. (2010). Longitudinal Modeling of Developmental Changes in Psychological Research. Current Directions in Psychological Science, 19(3), 149-154.
Johnson, W. (2010). Understanding the Genetics of Intelligence: Can Height Help? Can Corn Oil? Current Directions in Psychological Science, 19(3), 177-182.
Lavie, N. (2010). Attention, Distraction, and Cognitive Control Under Load. Current Directions in Psychological Science, 19(3), 143-148.
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010). Testing Predictions From Personality Neuroscience: Brain Structure and the Big Five. Psychological Science, 21(6), 820-828.
Goldstein, M. H., Waterfall, H. R., Lotem, A., Halpern, J. Y., Schwade, J. A., Onnis, L., & Edelman, S. (2010). General cognitive principles for learning structure in time and space. Trends in Cognitive Sciences, 14(6), 249-258.
Klingberg, T. (2010). Trainin and plasticity of working memory. Trends in Cognitive Sciences, 14 (7), 317-324
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gsm, working memory, attention, cognitive load, Big 5 personality, research bytes, longitudinal research
Ferrer, E., & McArdle, J. J. (2010). Longitudinal Modeling of Developmental Changes in Psychological Research. Current Directions in Psychological Science, 19(3), 149-154.
In this article we provide a review of recent advances in longitudinal models for multivariate change. We first claim the need for dynamic modeling approaches as a way to evaluate psychological theories. We then describe one such approach, latent change score (LCS) models, and illustrate their utility with a summary of research findings in various areas of psychological science. We then highlight the most prominent features of LCS models. We conclude the article with suggestions for future research on multivariate models of change that can enhance our understanding of psychological science.
Johnson, W. (2010). Understanding the Genetics of Intelligence: Can Height Help? Can Corn Oil? Current Directions in Psychological Science, 19(3), 177-182.
Although the subject is controversial, identifying the specific genes that contribute to general cognitive ability (GCA) has seemed to have good prospects, at least among psychological traits. GCA is reliably and validly measured and strongly heritable, and it shows genetically mediated physiological associations and developmental stability. To date, however, results have been disappointing. Human height shows these measurement characteristics even more strongly than GCA, yet data have indicated that no individual gene has more than trivial effects and this is also true for corn oil. The potential for environmental trigger of genetic expression, long recognized in evolutionary and developmental genetics, as applied to these seemingly disparate traits, can help us to understand the apparent contradiction between the heritability of intelligence and other psychological traits and the difficulty of identifying specific genetic effects.
Lavie, N. (2010). Attention, Distraction, and Cognitive Control Under Load. Current Directions in Psychological Science, 19(3), 143-148.
The extent to which people can focus attention in the face of irrelevant distractions has been shown to critically depend on the level and type of information load involved in their current task. The ability to focus attention improves under task conditions of high perceptual load but deteriorates under conditions of high load on cognitive control processes such as working memory. I review recent research on the effects of load on visual awareness and brain activity, including changing effects over the life span, and I outline the consequences for distraction and inattention in daily life and in clinical populations.
DeYoung, C. G., Hirsh, J. B., Shane, M. S., Papademetris, X., Rajeevan, N., & Gray, J. R. (2010). Testing Predictions From Personality Neuroscience: Brain Structure and the Big Five. Psychological Science, 21(6), 820-828.
We used a new theory of the biological basis of the Big Five personality traits to generate hypotheses about the association of each trait with the volume of different brain regions. Controlling for age, sex, and whole-brain volume, results from structural magnetic resonance imaging of 116 healthy adults supported our hypotheses for four of the five traits: Extraversion, Neuroticism, Agreeableness, and Conscientiousness. Extraversion covaried with volume of medial orbitofrontal cortex, a brain region involved in processing reward information. Neuroticism covaried with volume of brain regions associated with threat, punishment, and negative affect. Agreeableness covaried with volume in regions that process information about the intentions and mental states of other individuals. Conscientiousness covaried with volume in lateral prefrontal cortex, a region involved in planning and the voluntary control of behavior. These findings support our biologically based, explanatory model of the Big Five and demonstrate the potential of personality neuroscience (i.e., the systematic study of individual differences in personality using neuroscience methods) as a discipline
Goldstein, M. H., Waterfall, H. R., Lotem, A., Halpern, J. Y., Schwade, J. A., Onnis, L., & Edelman, S. (2010). General cognitive principles for learning structure in time and space. Trends in Cognitive Sciences, 14(6), 249-258.
An understanding of how the human brain produces cognition ultimately depends on knowledge of large-scale brain organization. Although it has long been assumed that cognitive functions are attributable to the isolated operations of single brain areas, we demonstrate that the weight of evidence has now shifted in support of the view that cognition results from the dynamic interactions of distributed brain areas operating in large-scale networks. We review current research on structural and functional brain organization, and argue that the emerging science of large-scale brain networks provides a coherent framework for understanding of cognition. Critically, this framework allows a principled exploration of how cognitive functions emerge from, and are constrained by, core structural and functional networks of the brain.
Klingberg, T. (2010). Trainin and plasticity of working memory. Trends in Cognitive Sciences, 14 (7), 317-324
Working memory (WM) capacity predicts performance in a wide range of cognitive tasks. Although WM capacity has been viewed as a constant trait, recent studies suggest that it can be improved by adaptive and extended training. This training is associated with changes in brain activity in frontal and parietal cortex and basal ganglia, as well as changes in dopamine receptor density. Transfer of the training effects to non-trained WM tasks is consistent with the notion of training-induced plasticity in a common neural network for WM. The observed training effects suggest that WM training could be used as a remediating intervention for individuals for whom low WM capacity is a limiting factor for academic performance or in everyday life.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gsm, working memory, attention, cognitive load, Big 5 personality, research bytes, longitudinal research
Research brief 7-26-10: CHC theory and measures (WJ III) found invariant (no psychometric bias) across blacks and whites
Kane, H. D., & Oakland, T. D. (2010). Group Differences in Cognitive Ability: A CHC Theory Framework. Mankind Quarterly, 50(4), 318-331.
Abstract
Abstract
The Cattell-Horn-Carroll (CHC) model of cognitive ability as represented in the Woodcock-Johnson Tests of Cognitive Ability-III (WJ-III) was examined for Black and White adults matched on various demographic variables. Although Whites performed higher than Blacks (i.e., race differences were found in test scores and accompanying factor means), the results of multisample confirmatory factor analyses found that the same constructs are measured in different groups. Therefore results are directly comparable, and in this sense measured differences can be interpreted as “real” differences on the dimensions that the test is meant to measure.Part of authors conclusions:
With respect to the primary purpose of this study, although White-Black differences in cognitive ability are affirmed in favor of Whites, these analyses reveal no source of psychometric bias (i.e., differences in loadings, test intercepts, and error variance). Constructs are represented adequately and without undo influence of error. The structural fidelity of the WJ-III factor model is psychometrically sound, making it a suitable instrument for psychologists when estimating general and broad cognitive abilities for individuals and groups. The reported indices of fit (e.g., TLI, GFI, and RMSEA) suggest that the threestratum CHC model fits the WJ-III data fairly well and provides evidence of construct validity. This finding substantiates a growing body of research literature that upholds the WJ-III as a strong representation of CHC theory (e.g., Edwards & Oakland, 2006; McGrew & Woodcock, 2001). Further, the data support Carroll’s (1993) belief that the CHC theory is essentially invariant across racial-ethnic groups. Notably, the group differences in test performance are smaller than in most other studies (e.g., Osborne & McGurk, 1982). This particular result is likely due to the samples being matched by parental education and occupational status. In the US, this kind of control is expected to remove approximately one third of the Black-White difference that may be expected in demographically representative samples (Jensen, 1998;Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gf, Gc, Gv, Ga, Gsm, Glr, Gs, Gq, Grw, WJ-R, WJ III, Woodcock-Johnson, WJ III NU, race and IQ, racial differences, psychometric bias, CFA, structural invariance
Lynn, 1998).
iPost: NIH assessment toolbox project
Interesting neuro assessment battery project at NIH link below
http://www.nihtoolbox.org/default.aspx
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Sunday, July 25, 2010
IQs Corner Recent Literature of Interest 07-25-10

Information regarding this feature, its basis, and the reasons for type of references included in each weekly installment can be found in a prior post.
Technorati Tags: psychology, school psychology, educational psychology, neuropsychology, research, recent literature, IQs Corner

Labels:
recent lit
iPost: Brain injury biomarkers test?
http://braininjury.blogs.com/braininjury/2010/07/new-test-to-detect-brain-injury-being-developed.html
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Friday, July 23, 2010
Gv (visual-spatial) abilities are important: STEM related research
Despite the finding that Gv tests on major individually administered IQ tests consistently fail to demonstrate strong correlations with standardized achievement tests, clinical experience and other research continues to indicate that strong Gv abilities are related to performance in complex higher-level areas of science, technology, engineering and mathematics. We in applied IQ test development just need to develop better measures of these specific Gv abilities or recognize that our current dependent achievement test variables fail to tap these domains of expertise. More from Lubinski on this topic.
Lubinski, D. (2010). Spatial ability and STEM: A sleeping giant for talent identification and development.
Personality and Individual Differences, 49(4), 344-351. (click here to read more)
Spatial ability is a powerful systematic source of individual differences that has been neglected in complex learning and work settings; it has also been neglected in modeling the development of expertise and creative accomplishments. Nevertheless, over 50 years of longitudinal research documents the important role that spatial ability plays in educational and occupational settings wherein sophisticated reasoning with figures, patterns, and shapes is essential. Given the contemporary push for developing STEM (science, technology, engineering, and mathematics) talent in the information age, an opportunity is available to highlight the psychological significance of spatial ability. Doing so is likely to inform research on aptitude-by-treatment interactions and Underwood’s (1975) idea to utilize individual differences as a crucible for theory construction. Incorporating spatial ability in talent identification procedures for advanced learning opportunities uncovers an under-utilized pool of talent for meeting the complex needs of an ever-growing technological world; furthermore, selecting students for advanced learning opportunities in STEM without considering spatial ability might be iatrogenic.
Article Outline
1. Spatial ability and STEM: decades of longitudinal research
2. Intellectually precocious youth
3. Discussion
4. Broader Psychological Implications
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gv, visual-spatial, visual processing, STEM, science, engineering, technology, mathematics
Lubinski, D. (2010). Spatial ability and STEM: A sleeping giant for talent identification and development.
Personality and Individual Differences, 49(4), 344-351. (click here to read more)
Spatial ability is a powerful systematic source of individual differences that has been neglected in complex learning and work settings; it has also been neglected in modeling the development of expertise and creative accomplishments. Nevertheless, over 50 years of longitudinal research documents the important role that spatial ability plays in educational and occupational settings wherein sophisticated reasoning with figures, patterns, and shapes is essential. Given the contemporary push for developing STEM (science, technology, engineering, and mathematics) talent in the information age, an opportunity is available to highlight the psychological significance of spatial ability. Doing so is likely to inform research on aptitude-by-treatment interactions and Underwood’s (1975) idea to utilize individual differences as a crucible for theory construction. Incorporating spatial ability in talent identification procedures for advanced learning opportunities uncovers an under-utilized pool of talent for meeting the complex needs of an ever-growing technological world; furthermore, selecting students for advanced learning opportunities in STEM without considering spatial ability might be iatrogenic.
Article Outline
1. Spatial ability and STEM: decades of longitudinal research
2. Intellectually precocious youth
3. Discussion
4. Broader Psychological Implications
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gv, visual-spatial, visual processing, STEM, science, engineering, technology, mathematics
Research Briefs 7-23-10: Psychology and academic freedom
Gottfredson, L. S. (2010). Lessons in academic freedom as lived experience. Personality and Individual Differences, 49(4), 272-280.
What is academic freedom, what guarantees it, and what would you do if your university violated yours? Few of us academics entertain these questions or ponder possible answers. This leaves us individually and collectively vulnerable to encroachments on our right to free and open inquiry. I use a case study from 1989–1994 to illustrate how violations of academic freedom develop, the typical pretexts used to justify them, and what is required to halt and reverse them. My aim is to help scholars recognize when academic freedom is at risk and how better to safeguard it in daily academic life. To this end, I describe the general social mechanisms that operate both inside and outside academe to selectively burden and suppress unpopular research. The case study provides concrete examples to illustrate six specific lessons. Like free speech in general, academic freedom (1) has maintenance costs, (2) is not self-enforcing, (3) is invoked today to stifle unwelcome speech, (4) is often violated by academic institutions, (5) is not often defended by academics themselves, and (6) yet, requires no heroic efforts for collective enjoyment if scholars consistently contribute small acts of support to prevent incursions.
Article Outline
1. Introduction
2. Preview of the six lessons and five sets of violations
3. Lesson 1. Academic freedom, like constitutionally-protected free speech, has maintenance costs
4. Lesson 2. Academic freedom is not self-enforcing
5. Lesson 3. Opposite to its intent, academic freedom is often invoked to restrict inquiry to “safe” ideas
6. Lesson 4. Academic freedom is often violated by academic institutions
7. Lesson 5. Academic freedom is often not defended by academic professionals themselves
8. Lesson 6. It does not take heroic efforts, just consistent ones, to sustain academic freedom
Hunt, E. (2010). The rights and responsibilities implied by academic freedom. Personality and Individual
Differences, 49(4), 264-271.
Academics enjoy freedom from retaliation for their statements that goes beyond the freedom accorded to other members of society. Academics are also often called upon to act as advisors, either to society as a whole or to public and private sector clients. This sets up a tension between freedom to speak and an obligation to speak responsibly. The problem can be acute in the field of individual differences, for findings related to individual differences touch upon the relations among different racial/ethnic groups, between genders, and have implications for educational and personnel policies. Examples are given of situations in which, in the author’s opinion, academics have abused their roles as expert advisors by speaking irresponsibly. At issue is not whether or not the person speaking reached a correct conclusion, but whether or not the evidence and reasoning about the evidence met reasonable standards for careful inquiry and analysis. Formal actions by governments or by university administration are seldom the answer. Standards enforced by professional societies are less problematical, but are far from complete solutions. The best way to handle the problem is to encourage open discussion of the issues involved, both between established academics and between faculty and students.
Article Outline
1. Introduction
2. The case of research on intelligence
3. Free speech protections and restrictions
4. The source of restrictions on free speech
5. The protection afforded by academic freedom
6. Illustrations
7. What to do about it
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, academic freedom
What is academic freedom, what guarantees it, and what would you do if your university violated yours? Few of us academics entertain these questions or ponder possible answers. This leaves us individually and collectively vulnerable to encroachments on our right to free and open inquiry. I use a case study from 1989–1994 to illustrate how violations of academic freedom develop, the typical pretexts used to justify them, and what is required to halt and reverse them. My aim is to help scholars recognize when academic freedom is at risk and how better to safeguard it in daily academic life. To this end, I describe the general social mechanisms that operate both inside and outside academe to selectively burden and suppress unpopular research. The case study provides concrete examples to illustrate six specific lessons. Like free speech in general, academic freedom (1) has maintenance costs, (2) is not self-enforcing, (3) is invoked today to stifle unwelcome speech, (4) is often violated by academic institutions, (5) is not often defended by academics themselves, and (6) yet, requires no heroic efforts for collective enjoyment if scholars consistently contribute small acts of support to prevent incursions.
Article Outline
1. Introduction
2. Preview of the six lessons and five sets of violations
3. Lesson 1. Academic freedom, like constitutionally-protected free speech, has maintenance costs
4. Lesson 2. Academic freedom is not self-enforcing
5. Lesson 3. Opposite to its intent, academic freedom is often invoked to restrict inquiry to “safe” ideas
6. Lesson 4. Academic freedom is often violated by academic institutions
7. Lesson 5. Academic freedom is often not defended by academic professionals themselves
8. Lesson 6. It does not take heroic efforts, just consistent ones, to sustain academic freedom
Hunt, E. (2010). The rights and responsibilities implied by academic freedom. Personality and Individual
Differences, 49(4), 264-271.
Academics enjoy freedom from retaliation for their statements that goes beyond the freedom accorded to other members of society. Academics are also often called upon to act as advisors, either to society as a whole or to public and private sector clients. This sets up a tension between freedom to speak and an obligation to speak responsibly. The problem can be acute in the field of individual differences, for findings related to individual differences touch upon the relations among different racial/ethnic groups, between genders, and have implications for educational and personnel policies. Examples are given of situations in which, in the author’s opinion, academics have abused their roles as expert advisors by speaking irresponsibly. At issue is not whether or not the person speaking reached a correct conclusion, but whether or not the evidence and reasoning about the evidence met reasonable standards for careful inquiry and analysis. Formal actions by governments or by university administration are seldom the answer. Standards enforced by professional societies are less problematical, but are far from complete solutions. The best way to handle the problem is to encourage open discussion of the issues involved, both between established academics and between faculty and students.
Article Outline
1. Introduction
2. The case of research on intelligence
3. Free speech protections and restrictions
4. The source of restrictions on free speech
5. The protection afforded by academic freedom
6. Illustrations
7. What to do about it
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, academic freedom
Thursday, July 22, 2010
iPost: Predictive ability of WISCIV GAI in gifted
http://psycnet.apa.org/journals/spq/25/2/119/
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Sunday, July 18, 2010
On the road again--blogging lite July 18-21

I will be on the road (working) again from July 18-21.
I don't expect much time to blog...except for possible "push" type FYI posts re: content posted at other blogs.....or...mobile blogging (iPosts: check out the link.....it is very cool...but, of course, I tend to be a tech nerd)......
I shall return.
Technorati Tags: psychology, IQs Corner, Intelligence, travel
Saturday, July 17, 2010
Friday, July 16, 2010
IQs Corner Recent Literature of Interest 07-16-10

Information regarding this feature, its basis, and the reasons for type of references included in each weekly installment can be found in a prior post.
Technorati Tags: psychology, school psychology, educational psychology, neuropsychology, research, recent literature, IQs Corner

Labels:
recent lit
New SLD identification model: Wayne County uses CHC theory for cognitive component
Many school districts are working to implement the new IDEA law and regulations regarding SLD identification in the context of a Tier-based Response to Intervention (RTI) model. Today I learned of on school system (Wayne County) that uses, for the cognitive strenghts and weaknesses component, the Cattell-Horn-Carroll (CHC) model. Information regarding their system can be found at their web page.
I would be interested in hearing of other school systems that have organized the cognitive pattern of strengths and weaknesses SLD component around the CHC model. Contact me at iap@earthlink.net if you would have something to share and that I could share with IQs Corner readers.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gf, Gc, Gv, Ga, Gsm, Glr, Gs, Gq, Grw, WJ-R, WJ III, Woodcock-Johnson, WJ III NU, SLD, RTI, response to intervention
I would be interested in hearing of other school systems that have organized the cognitive pattern of strengths and weaknesses SLD component around the CHC model. Contact me at iap@earthlink.net if you would have something to share and that I could share with IQs Corner readers.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, Gf, Gc, Gv, Ga, Gsm, Glr, Gs, Gq, Grw, WJ-R, WJ III, Woodcock-Johnson, WJ III NU, SLD, RTI, response to intervention
Labels:
CHC theory,
LD,
RTI
Thursday, July 15, 2010
Current research in Cattell-Horn-Carroll (CHC) based intelligence testing: Special PITS isue is out
I'm excited to announce that the special issue of Psychology in the Schools, Current Research in Cattell-Horn-Carroll-Based Assessment (guest editors where Jocelyn Newton and myself), is now published. Yippeee. To be honest, Dr. Newton deserves the major credit....she did all the heavy lifting and I road her coat tails. Also thanks to Dr. David McIntosh for suggesting and overseeing the special issue
A review of the TOC can be found by clicking here. A copy of the article (Cattell-Horn-Carroll cognitive achievement relations: What we have learned from the past 20 years of research) I co-authored with Barb Wendling can be found by clicking here and the introduction to this issue I co-authored with Dr. Newton is available here.
If you do not have access to this journal and would like to read 1 or more of the articles, I'd be willing to privately share PDF copies in exchange for a guest blog post review here at IQ's Corner. Now how can folks resist such an offer?....to learn more and to become a guest blogger. It doesn't get any better.
Enjoy.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, school achievement, general intelligence, Gf, Gc, Gv, Ga, Gsm, Glr, Gs, Gq, Grw, Psychology in the Schools, learning disabilities, RTI
A review of the TOC can be found by clicking here. A copy of the article (Cattell-Horn-Carroll cognitive achievement relations: What we have learned from the past 20 years of research) I co-authored with Barb Wendling can be found by clicking here and the introduction to this issue I co-authored with Dr. Newton is available here.
If you do not have access to this journal and would like to read 1 or more of the articles, I'd be willing to privately share PDF copies in exchange for a guest blog post review here at IQ's Corner. Now how can folks resist such an offer?....to learn more and to become a guest blogger. It doesn't get any better.
Enjoy.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, CHC, Cattell-Horn-Carroll, intelligence, cognition, IQ, IQ tests, school achievement, general intelligence, Gf, Gc, Gv, Ga, Gsm, Glr, Gs, Gq, Grw, Psychology in the Schools, learning disabilities, RTI
Labels:
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g (gen IQ),
g+specific,
Ga,
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Gf,
Glr,
Gq,
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Gs,
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WJ III,
WJ III NU,
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Quantoids corner: Intro to hierarchical linear modeling (HLM)
I LOVE it when more applied journals publish articles where complex statistical methods are presented to a less statistically oriented audience, as I often find these "quanatoid explanations for dummies" an excellent introduction to complex statistical methods. Today I discovered that Gifted Child Quarterly has published a brief two-part series of articles that provide a nice introduction to HLM. I've never run HLM models, so I found the introduction very helpful. So much so that I might run some HLM on some appropriate datasets I have just to see it work.
Below are the two articles. Enjoy. Kudos to GCQ and Dr. McCoach.
McCoach, D. B. & Adelson, J. L. Dealing with dependence (Part 1): Understanding the effects of clustered data. Gifted Child Quarterly, 54(2), 152-155.
McCoach, D. B. (2010). Dealing With Dependence (Part II): A Gentle Introduction to Hierarchical Linear
Modeling. Gifted Child Quarterly, 54(3), 252-256.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, statistics, HLM, hierarchical linear modeling, gifted, Gifted Child Quarterly, quatoids corner
Below are the two articles. Enjoy. Kudos to GCQ and Dr. McCoach.
McCoach, D. B. & Adelson, J. L. Dealing with dependence (Part 1): Understanding the effects of clustered data. Gifted Child Quarterly, 54(2), 152-155.
This article provides a conceptual introduction to the issues surrounding the analysis of clustered (nested) data. We define the intraclass correlation coefficient (ICC) and the design effect, and we explain their effect on the standard error. When the ICC is greater than 0, then the design effect is greater than 1. In such a scenario, the standard error produced under the assumption of independence is underestimated. This increases the Type I error rate. We provide a short illustration of the effect of non-independence on the standard error. We show that after accounting for the design effect, our decision about the statistical significance of the test statistic changes. When we fail to account for the clustered nature of the data, we conclude that the difference between the two groups is statistically significant. However, once we adjust the standard error for the design effect, the difference is no longer statistically significant.
McCoach, D. B. (2010). Dealing With Dependence (Part II): A Gentle Introduction to Hierarchical Linear
Modeling. Gifted Child Quarterly, 54(3), 252-256.
In education, most naturally occurring data are clustered within contexts. Students are clustered within classrooms, classrooms are clustered within schools, and schools are clustered within districts. When people are clustered within naturally occurring organizational units such as schools, classrooms, or districts, the responses of people from the same cluster are likely to exhibit some degree of relatedness with each other. The use of hierarchical linear modeling allows researchers to adjust for and model this non-independence. Furthermore, it may be of great substantive interest to try to understand the degree to which people from the same cluster are similar to each other and then to try to identify variables that help us to understand differences both within and across clusters. In HLM, we endeavor to understand and explain between- and within-cluster variability of an outcome variable of interest. We can also use predictors at both the individual level (level 1), and the contextual level (level 2) to explain the variance in the dependent variable. This article presents a simple example using a real data set and walk through the interpretation of a simple hierarchical linear model to illustrate the utility of the technique.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, statistics, HLM, hierarchical linear modeling, gifted, Gifted Child Quarterly, quatoids corner
Labels:
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Wednesday, July 14, 2010
Research bytes 7-14-10: Early detection and prediction of academic problems-special issue of JLD
Thomson, J. M., & Hogan, T. P. (2010). Introduction: Advances in Early Detection of Reading Risk. Journal of Learning Disabilities, 43(4), 291-293.
Adlof, S. M., Catts, H. W., & Lee, J. (2010). Kindergarten Predictors of Second Versus Eighth Grade Reading Comprehension Impairments. Journal of Learning Disabilities, 43(4), 332-345.
Corriveau, K. H., Goswami, U., & Thomson, J. M. (2010). Auditory Processing and Early Literacy Skills in a Preschool and Kindergarten Population. Journal of Learning Disabilities, 43(4), 369-382.
Hogan, T. P. (2010). A short report: Word-level phonological and lexical characteristics interact to influence phoneme awareness
Liu, P. D., McBrideChang, C., Wong, A. M. Y., Tardif, T., Stokes, S. F., Fletcher, P., & Shu, H. (2010). Early Oral Language Markers of Poor Reading Performance in Hong Kong Chinese Children. Journal of Learning
Disabilities, 43(4), 322-331.
Smith, S. L., Roberts, J. A., Locke, J. L., & Tozer, R. (2010). An Exploratory Study of the Development of Early Syllable Structure in Reading-Impaired Children. Journal of Learning Disabilities, 43(4), 294-307.
Torppa, M., Lyytinen, P., Erskine, J., Eklund, K., & Lyytinen, H. (2010). Language Development, Literacy Skills,
and Predictive Connections to Reading in Finnish Children With and Without Familial Risk for Dyslexia.
Journal of Learning Disabilities, 43(4), 308-321.
Dynamic Relations, and Advanced Methods. Journal of Learning Disabilities, 43(4), 383-386.
Adlof, S. M., Catts, H. W., & Lee, J. (2010). Kindergarten Predictors of Second Versus Eighth Grade Reading Comprehension Impairments. Journal of Learning Disabilities, 43(4), 332-345.
Multiple studies have shown that kindergarten measures of phonological awareness and alphabet knowledge are good predictors of reading achievement in the primary grades. However, less attention has been given to the early predictors of later reading achievement. This study used a modified best-subsets variable-selection technique to examine kindergarten predictors of early versus later reading comprehension impairments. Participants included 433 children involved in a longitudinal study of language and reading development. The kindergarten test battery assessed various language skills in addition to phonological awareness, alphabet knowledge, naming speed, and nonverbal cognitive ability. Reading comprehension was assessed in second and eighth grades. Results indicated that different combinations of variables were required to optimally predict second versus eighth grade reading impairments. Although some variables effectively predicted reading impairments in both grades, their relative contributions shifted over time. These results are discussed in light of the changing nature of reading comprehension over time. Further research will help to improve the early identification of later reading disabilities.
Corriveau, K. H., Goswami, U., & Thomson, J. M. (2010). Auditory Processing and Early Literacy Skills in a Preschool and Kindergarten Population. Journal of Learning Disabilities, 43(4), 369-382.
Although the relationship between auditory processing and reading-related skills has been investigated in school-age populations and in prospective studies of infants, understanding of the relationship between these variables in the period immediately preceding formal reading instruction is sparse. In this cross-sectional study, auditory processing, phonological awareness, early literacy skills, and general ability were assessed in a mixed sample of 88 three- to six-year-old children both cross-sectionally and longitudinally. Results from both cross-sectional and longitudinal analyses suggest the importance of early auditory rise time sensitivity in developing phonological awareness skills, especially in the development of rhyme awareness.
Hogan, T. P. (2010). A short report: Word-level phonological and lexical characteristics interact to influence phoneme awareness
In this study, we examined the influence of word-level phonological and lexical characteristics on early phoneme awareness. Typically developing children, ages 61 to 78 months, completed a phoneme-based, odd-one-out task that included consonant—vowel—consonant word sets (e.g., “chair—chain—ship”) that varied orthogonally by a phonological characteristic, sound contrast similarity (similar vs. dissimilar), and a lexical characteristic, neighborhood density (dense vs. sparse). In a subsample of the participants—those with the highest vocabularies—results were in line with a predicted interactive effect of phonological and lexical characteristics on phoneme awareness performance: word sets contrasting similar sounds were less likely to yield correct responses in words from sparse neighborhoods than words from dense neighborhoods. Word sets contrasting dissimilar sounds were most likely to yield correct responses regardless of the words’ neighborhood density. Based on these findings, theories of early phoneme awareness should consider both word-level and child-level influences on performance. Attention to these influences is predicted to result in more sensitive and specific measures of reading risk.
Liu, P. D., McBrideChang, C., Wong, A. M. Y., Tardif, T., Stokes, S. F., Fletcher, P., & Shu, H. (2010). Early Oral Language Markers of Poor Reading Performance in Hong Kong Chinese Children. Journal of Learning
Disabilities, 43(4), 322-331.
This study investigated the extent to which language skills at ages 2 to 4 years could discriminate Hong Kong Chinese poor from adequate readers at age 7. Selected were 41 poor readers (age M = 87.6 months) and 41 adequate readers (age M = 88.3 months). The two groups were matched on age, parents’ education levels, and nonverbal intelligence. The following language tasks were tested at different ages: vocabulary checklist and Cantonese articulation test at age 2; nonword repetition, Cantonese articulation, and receptive grammar at age 3; and nonword repetition, receptive grammar, sentence imitation, and story comprehension at age 4. Significant differences between the poor and adequate readers were found in the age 2 vocabulary knowledge, age 3 Cantonese articulation, and age 4 receptive grammar skill, sentence imitation, and story comprehension. Among these measures, sentence imitation showed the greatest power in discriminating poor and adequate readers.
Smith, S. L., Roberts, J. A., Locke, J. L., & Tozer, R. (2010). An Exploratory Study of the Development of Early Syllable Structure in Reading-Impaired Children. Journal of Learning Disabilities, 43(4), 294-307.
Babbling between the ages of 8 and 19 months was examined in 19 children, 13 of whom were at high risk for reading disorder (RD) and 6 normally reading children at low familial risk for RD. Development of syllable complexity was examined at five periods across this 11-month window. Results indicated that children who later evidenced RD produced a lower proportion of canonical utterances and less complex syllable structures than children without RD. As syllable complexity is an early indicator of phonological sophistication, differences at this level may offer a window into how the phonological system of children with RD is structured. Future directions for this line of research are discussed
Torppa, M., Lyytinen, P., Erskine, J., Eklund, K., & Lyytinen, H. (2010). Language Development, Literacy Skills,
and Predictive Connections to Reading in Finnish Children With and Without Familial Risk for Dyslexia.
Journal of Learning Disabilities, 43(4), 308-321.
Discriminative language markers and predictive links between early language and literacy skills were investigated retrospectively in the Jyväskylä Longitudinal Study of Dyslexia in which children at familial risk for dyslexia have been followed from birth. Three groups were formed on the basis of 198 children’s reading and spelling status. One group of children with reading disability (RD; n = 46) and two groups of typical readers from nondyslexic control (TRC; n = 84) and dyslexic families (TRD; n = 68) were examined from age 1.5 years to school age. The RD group was outperformed by typical readers on numerous language and literacy measures (expressive and receptive language, morphology, phonological sensitivity, RAN, and letter knowledge) from 2 years of age onward. The strongest predictive links emerged from receptive and expressive language to reading via measures of letter naming, rapid naming, morphology, and phonological awareness.vanderLely, H. K. J., & Marshall, C. R. (2010). Assessing Component Language Deficits in the Early Detection of Reading Difficulty Risk. Journal of Learning Disabilities, 43(4), 357-368.
This article focuses on some of the linguistic components that underlie letter-sound decoding skills and reading comprehension: specifically phonology, morphology, and syntax. Many children who have reading difficulties had language deficits that were detectable before they began reading. Early identification of language difficulties will therefore help identify children at risk of reading failure. Using a developmental psycholinguistic framework, the authors provide a model of how syntax, morphology, and phonology break down in children with language impairments. The article reports on a screening test of these language abilities for preschool or young school-aged children that identifies those at risk for literacy problems and in need of further assessment.Hogan, T. P., & Thomson, J. M. (2010). Epilogue to Journal of Learning Disabilities Special Edition ''Advances in the Early Detection of Reading Risk'': Future Advances in the Early Detection of Reading Risk: Subgroups,
Dynamic Relations, and Advanced Methods. Journal of Learning Disabilities, 43(4), 383-386.
Six studies and one synthesis focused on early identification of reading impairment in this special edition. A familiar theme emerged: reading involves multiple subsystems that dynamically interact across development, making early identification a “moving target” (cf. Speece, 2005). Based on the cumulative findings presented in this edition, we pose five key considerations for future advances in the early detection of reading risk: (a) attention to the definition of reading and the heterogeneity of poor readers; (b) longitudinal dynamic relations; (c) application of advanced, theory-driven methods and statistical models; (d) early identification that leads to prescriptive early intervention; and (e) early identification in a multilingual, multicultural population.Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, Cattell-Horn-Carroll, factor analysis, IQs Corner, IQ, IQ tests, IQ scores, school achievement, early screening, at risk learners, prediction of achievement, early detection of learning problems
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Example of task analysis of math problem-solving
The following article, although quite technical and quantoid in nature, includes an interesting task-analysis flow chart of mathematical problem solving that might serve as a conceptual model for analyzing cognitive and achievement tasks....the figure caught my attention.
Daniel, R. C., & Embretson, S. E. (2010). Designing Cognitive Complexity in Mathematical Problem-Solving Items. Applied Psychological Measurement, 34(5), 348-364.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, Cattell-Horn-Carroll, factor analysis, IQs Corner, IQ, IQ tests, IQ scores, math achievement, dyscalculia, math problem solving
[Double click image to enlarge]
Daniel, R. C., & Embretson, S. E. (2010). Designing Cognitive Complexity in Mathematical Problem-Solving Items. Applied Psychological Measurement, 34(5), 348-364.
Cognitive complexity level is important for measuring both aptitude and achievement in large-scale testing. Tests for standards-based assessment of mathematics, for example, often include cognitive complexity level in the test blueprint. However, little research exists on how mathematics items can be designed to vary in cognitive complexity level. In fact, determining the cognitive complexity level of items is usually based on correspondence to definitions rather than on empirically and theoretically justifiable variables that can predict item difficulty. In the current study, mathematical problem-solving items were designed for varying cognitive complexity levels based on a cognitive model of item processing. Structural variants of item models were designed to vary on two aspects of the cognitive model, the equation source and the number of subgoals. Participants were randomly assigned to test forms that contained different structural variants of the item models. Results from the linear logistic test model, the two-parameter-logistic—constrained model, and a corresponding linear mixed modeling procedure indicated that the item design variables affected both item difficulty and response time. Implications of the results for using structural variants in item generation and for the plausibility of the hypothesized cognitive model are discussed.
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, Cattell-Horn-Carroll, factor analysis, IQs Corner, IQ, IQ tests, IQ scores, math achievement, dyscalculia, math problem solving
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New book on intelligence by Earl Hunt: Available November 2010
I just learned of an exciting new book on intelligence by a giant in the field, Earl Hunt. The book Human Intelligence will be available this November from Cambridge University Press.
I look forward to reviewing the contents when I can secure a copy. I have added the book to IQs Corner Book Store
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, Cattell-Horn-Carroll, factor analysis, IQs Corner, IQ, IQ tests, IQ scores, Earl Hunt, human intelligence
I look forward to reviewing the contents when I can secure a copy. I have added the book to IQs Corner Book Store
Technorati Tags: Psychology, school psychology, developmental psychology, educational psychology, forensic psychology, neuropsychology, special education, intelligence, cognitive abilities, cognition, intelligence theories, CHC theory, Cattell-Horn-Carroll, factor analysis, IQs Corner, IQ, IQ tests, IQ scores, Earl Hunt, human intelligence
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Tuesday, July 13, 2010
iPost: PEBS neuroethics roundup
Good stuff at link below
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Saturday, July 10, 2010
iPost: Bilingualism enhances executive functions?
Story at SHARP BRAINS link below.
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