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Showing 1 to 15 of 47 results Save | Export
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Emily Mather; Shane Lindsay – Infant and Child Development, 2025
There is widespread evidence that children display a mutual exclusivity response upon encountering new words. Children displaying this behaviour will select a novel, name-unknown object in response to a novel label, rather than a familiar, name-known object. The mutual exclusivity response has been viewed as a means of fast-mapping…
Descriptors: Children, Memory, Retention (Psychology), Vocabulary Development
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Minju Kim; Adena Schachner – Developmental Science, 2025
Listening to music activates representations of movement and social agents. Why? We test whether causal reasoning plays a role, and find that from childhood, people can intuitively reason about how musical sounds were generated, inferring the events and agents that caused the sounds. In Experiment 1 (N = 120, pre-registered), 6-year-old children…
Descriptors: Causal Models, Abstract Reasoning, Thinking Skills, Music
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Verhaar, Erik; Medendorp, Wijbrand Pieter; Hunnius, Sabine; Stapel, Janny C. – Developmental Science, 2022
If cues from different sensory modalities share the same cause, their information can be integrated to improve perceptual precision. While it is well established that adults exploit sensory redundancy by integrating cues in a Bayes optimal fashion, whether children under 8 years of age combine sensory information in a similar fashion is still…
Descriptors: Bayesian Statistics, Causal Models, Statistical Inference, Visual Perception
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Kaplan, David; Chen, Jianshen; Lyu, Weicong; Yavuz, Sinan – Large-scale Assessments in Education, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
David Kaplan; Jianshen Chen; Weicong Lyu; Sinan Yavuz – Grantee Submission, 2023
The purpose of this paper is to extend and evaluate methods of "Bayesian historical borrowing" applied to longitudinal data with a focus on parameter recovery and predictive performance. Bayesian historical borrowing allows researchers to utilize information from previous data sources and to adjust the extent of borrowing based on the…
Descriptors: Bayesian Statistics, Longitudinal Studies, Children, Surveys
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Thompson, Yutian T.; Song, Hairong; Shi, Dexin; Liu, Zhengkui – Educational and Psychological Measurement, 2021
Conventional approaches for selecting a reference indicator (RI) could lead to misleading results in testing for measurement invariance (MI). Several newer quantitative methods have been available for more rigorous RI selection. However, it is still unknown how well these methods perform in terms of correctly identifying a truly invariant item to…
Descriptors: Measurement, Statistical Analysis, Selection, Comparative Analysis
Atmaca, Furkan; Baloglu, Mustafa – Gifted Child Quarterly, 2022
We compared the Wechsler scores of individuals with twice-exceptionality (2e) and giftedness using a three-level Bayesian meta-analysis. Ninety-five effect sizes were calculated from 15 studies (n = 2,106). Results show that individuals with 2e who have learning disabilities perform lower than individuals with giftedness in Full-Scale Intelligence…
Descriptors: Meta Analysis, Gifted Disabled, Intelligence Quotient, Identification
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Kastner, Itamar; Adriaans, Frans – Cognitive Science, 2018
Statistical learning is often taken to lie at the heart of many cognitive tasks, including the acquisition of language. One particular task in which probabilistic models have achieved considerable success is the segmentation of speech into words. However, these models have mostly been tested against English data, and as a result little is known…
Descriptors: Role, Phonemes, Contrastive Linguistics, English
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Moreno-Estevaa, Enrique Garcia; White, Sonia L. J.; Wood, Joanne M.; Black, Alex A. – Frontline Learning Research, 2018
In this research, we aimed to investigate the visual-cognitive behaviours of a sample of 106 children in Year 3 (8.8 ± 0.3 years) while completing a mathematics bar-graph task. Eye movements were recorded while children completed the task and the patterns of eye movements were explored using machine learning approaches. Two different techniques of…
Descriptors: Artificial Intelligence, Man Machine Systems, Mathematics Education, Eye Movements
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Dombrowski, Stefan C.; Golay, Philippe; McGill, Ryan J.; Canivez, Gary L. – Psychology in the Schools, 2018
Bayesian structural equation modeling (BSEM) was used to investigate the latent structure of the Differential Ability Scales-Second Edition core battery using the standardization sample normative data for ages 7-17. Results revealed plausibility of a three-factor model, consistent with publisher theory, expressed as either a higher-order (HO) or a…
Descriptors: Structural Equation Models, Bayesian Statistics, Factor Analysis, Aptitude Tests
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Friede, Tim; Röver, Christian; Wandel, Simon; Neuenschwander, Beat – Research Synthesis Methods, 2017
Meta-analyses in orphan diseases and small populations generally face particular problems, including small numbers of studies, small study sizes and heterogeneity of results. However, the heterogeneity is difficult to estimate if only very few studies are included. Motivated by a systematic review in immunosuppression following liver…
Descriptors: Meta Analysis, Diseases, Medical Research, Research Problems
Zhang, Zhiyong – Grantee Submission, 2016
Growth curve models are widely used in social and behavioral sciences. However, typical growth curve models often assume that the errors are normally distributed although non-normal data may be even more common than normal data. In order to avoid possible statistical inference problems in blindly assuming normality, a general Bayesian framework is…
Descriptors: Bayesian Statistics, Models, Statistical Distributions, Computation
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Marcoulides, Katerina M.; Grimm, Kevin J. – Educational and Psychological Measurement, 2017
Synthesizing results from multiple studies is a daunting task during which researchers must tackle a variety of challenges. The task is even more demanding when studying developmental processes longitudinally and when different instruments are used to measure constructs. Data integration methodology is an emerging field that enables researchers to…
Descriptors: Growth Models, Longitudinal Studies, Mathematics Skills, Achievement Tests
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Liu, Haiyan; Zhang, Zhiyong; Grimm, Kevin J. – Grantee Submission, 2016
Growth curve modeling provides a general framework for analyzing longitudinal data from social, behavioral, and educational sciences. Bayesian methods have been used to estimate growth curve models, in which priors need to be specified for unknown parameters. For the covariance parameter matrix, the inverse Wishart prior is most commonly used due…
Descriptors: Bayesian Statistics, Computation, Statistical Analysis, Growth Models
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Kim, Dan; Opfer, John E. – Developmental Psychology, 2017
Representations of numerical value have been assessed by using bounded (e.g., 0-1,000) and unbounded (e.g., 0-?) number-line tasks, with considerable debate regarding whether 1 or both tasks elicit unique cognitive strategies (e.g., addition or subtraction) and require unique cognitive models. To test this, we examined how well a mixed log-linear…
Descriptors: Computation, Numbers, Children, Cognitive Development
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