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Purpose: Bayesian-based models for diagnosis are common in medicine but have not been incorporated into identification models for dyslexia. The purpose of the present study was to evaluate Bayesian identification models that included a broader set of predictors and that capitalized on recent developments in modeling the prevalence of dyslexia. Method: Model-based meta-analysis was used to create a composite correlation matrix that included common predictors of dyslexia such as decoding, phonological awareness, oral language, but also included response to intervention (RTI) and family risk for dyslexia. Bayesian logistic regression models were used to predict poor reading comprehension, unexpectedly poor reading comprehension, poor decoding, and unexpectedly poor decoding, all at two levels of severity. Results: Most predictors made independent and substantial contributions to prediction, supporting models of dyslexia that rely on multiple rather than single indicators. RTI was the strongest predictor of poor reading comprehension and unexpectedly poor reading comprehension. Phonological awareness was the strongest predictor of poor decoding and unexpectedly poor decoding, followed closely by family risk. Conclusion: Bayesian-based models are a promising tool for implementing multiple-indicator models of identification. Ideas for improving prediction and implications for theory and practice are discussed.

Many of the analytical models commonly used in educational research often aim to maximize explained variance and identify variable importance within models. These models are useful for understanding general ideas and trends, but give limited insight into the individuals within said models. Data envelopment analysis (DEA), is a method rooted in organizational management that makes such insights possible. Unlike models alluded to above, DEA does not explain variance. Instead, it explains how efficiently an individual utilizes their inputs to produce outputs, and identifies which input is not being utilized optimally. This paper provides a history and usages of DEA from fields outside of education, and describes the math and processes behind it. This paper then extends DEA's usage into the educational field using a study on child reading ability. Using students from the Project KIDS dataset (n = 1987), DEA is demonstrated using a simple view of reading framework, identifying individual efficiency levels in using reading-based skills to achieve reading comprehension, determining which skills are being underutilized, and classifying new subsets of readers. New subsets of readers were identified using this method, with implications for more targeted interventions.

Despite decades of research, it has been difficult to achieve consensus on a definition of common learning disabilities such as dyslexia. This lack of consensus represents a fundamental problem for the field. Our approach to addressing this issue is to use model-based meta-analyses and Bayesian models with informative priors to combine the results of a large number of studies for the purpose of yielding a more stable and well-supported conceptualization of reading disability. A prerequisite to implementing these models is establishing informative priors for dyslexia. We illustrate a new approach for doing so based on the known distribution of the difference between correlated variables, and use this distribution to determine the proportion of poor readers whose poor reading is unexpected (i.e., likely to be due to dyslexia) as opposed to expected.

We report findings of two exploratory validation studies of a revised instrument: the "Student Risk Screening Scale for Early Childhood" version (SRSS-EC). The SRSS-EC was modified to reflect characteristics of externalizing and internalizing behaviors manifested by preschool-age children. In Study 1, we explored the reliability of SRSS-IE ("Student Risk Screening Scale-Internalizing and Externalizing") 14 scores by examining item-level data, internal consistency, and factor structure using exploratory factor analysis with 489 preschool-age students. Results supported retention of 11 items, resulting in the SRSS-EC 11 (with SRSS-EC E7 externalizing subscale and SRSS-EC I4 internalizing subscale). Next, we established convergent validity of the SRSS-EC 11 with two well-established screening tools: the Strengths and Difficulties Questionnaire and the Early Screening Project. In Study 2, we reported findings of a confirmatory factor analysis and a subsequent convergent validity study with 737 preschool-age students to determine generalizability. We offered limitations and future directions.

Executive function is a broad construct that encompasses various processes involved in goal-directed behaviour in non-routine situations (Banich, 2009). The present study uses a sample of 560 5- to 16-year-old twin pairs ( M = 11.14, SD = 2.53): 219 monozygotic twin pairs (114 female; 105 male) and 341 dizygotic twin pairs (136 female, 107 male; 98 opposite sex) to extend prior literature by providing information about the factor structure and the genetic and environmental architecture of the Behavior Rating Inventory of Executive Function ( BRIEF; Gioia et al., 2000, Child Neuropsychol., 6, 235; Gioia et al., 2000, Behavior rating inventory of executive function, Lutz, FL: Psychological Assessment Resources), a multifaceted rating scale of everyday executive functions. Phenotypic results revealed a 9-scale, 3-factor model best represents the BRIEF structure within the current sample. Results of the genetically sensitive analyses indicated the presence of rater bias/contrast effects for the Initiate, Working Memory, and Task-Monitor scales. Additive genetic and non-shared environmental influences were present for the Initiate, Plan/Organize, Organization of Materials, Shift, and Monitor and Self-Monitor scales. Influences on Emotional Control were solely environmental. Interestingly, the aetiological architecture observed was similar to that of performance-based measures of executive function. This observed similarity provided additional evidence for the usefulness of the BRIEF as a measure of 'everyday' executive function. [ABSTRACT FROM AUTHOR]

This study examines the response patterns of 288 Spanish-English dual language learners on a standardized test of receptive Spanish vocabulary. Investigators analyzed responses to 54 items on the Test de Vocabulario en Imagenes (TVIP) (Dunn & Dunn, 2007) focusing on differential accuracy on items influenced by a) cross-linguistic overlap, b) context (home/school), and c) word frequency in Spanish. The response patterns showed cross-linguistic overlap in phonology was a significant predictor of accuracy at the item level. After accounting for item number (expected difficulty level), context of exposure was a significant predictor of the likelihood of obtaining a correct response. Spanish word frequency was not a significant predictor of accuracy. The current findings substantiate the influence of cross-linguistic overlap in phonology and context on Spanish vocabulary recognition by Spanish-English speaking children. Children were more likely to obtain correct responses on lexical items that were associated with the home context. Researchers and practitioners should consider phonological cross-linguistic overlap in addition to context of word exposure and word frequency when designing and utilizing vocabulary assessments for children from linguistic minority backgrounds.

Cigarette smoking during pregnancy is a major public health concern, resulting in detrimental health effects in the mother and her offspring. The adverse behavioral consequences for children include increased risk for attention deficit hyperactivity disorder, working memory deficits, epilepsy, novelty-seeking, and risk-taking behaviors. Some of these behavioral conditions are consistent with an imbalance in frontal cortical excitatory (glutamate) and inhibitory (GABA) neurotransmitter signaling. We used a GAD67-GFP knock-in mouse model to examine if developmental nicotine exposure alters frontal cortical GABA neuron numbers, GABA-to-non-GABA neuron ratio and behavioral phenotypes. Female mice were exposed to nicotine (100 or 200 μg/mL) in drinking water beginning 3 weeks prior to breeding and until 3 weeks postpartum. Male and female offspring were examined beginning at 60 days of age. The nicotine exposure produced dose-dependent decreases in GABA-to-non-GABA neuron ratios in the prefrontal and medial prefrontal cortices without perturbing the intrinsic differences in cortical thickness and laminar distribution of GABA or non-GABA neurons between these regions. A significant increase in exploratory behavior and a shift toward "approach" in the approach-avoidance paradigm were also observed. Thus, developmental nicotine exposure shifts the cortical excitation-inhibition balance toward excitation and produces behavioral changes consistent with novelty-seeking behavior., (© The Author(s) 2019. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permission@oup.com.)