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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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Natesan Batley, Prathiba; Shukla Mehta, Smita; Hitchcock, John H. – Behavioral Disorders, 2021
Single case experimental design (SCED) is an indispensable methodology when evaluating intervention efficacy. Despite long-standing success with using visual analyses to evaluate SCED data, this method has limited utility for conducting meta-analyses. This is critical because meta-analyses should drive practice and policy in behavioral disorders…
Descriptors: Bayesian Statistics, Research Design, Effect Size, Meta Analysis
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Shi, Linyu; Chu, Haitao; Lin, Lifeng – Research Synthesis Methods, 2020
Publication bias threatens meta-analysis validity. It is often assessed via the funnel plot; an asymmetric plot implies small-study effects, and publication bias is one cause of the asymmetry. Egger's regression test is a widely used tool to quantitatively assess such asymmetry. It examines the association between the observed effect sizes and…
Descriptors: Bayesian Statistics, Meta Analysis, Effect Size, Publications
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Seide, Svenja E.; Jensen, Katrin; Kieser, Meinhard – Research Synthesis Methods, 2020
The performance of statistical methods is often evaluated by means of simulation studies. In case of network meta-analysis of binary data, however, simulations are not currently available for many practically relevant settings. We perform a simulation study for sparse networks of trials under between-trial heterogeneity and including multi-arm…
Descriptors: Bayesian Statistics, Meta Analysis, Data Analysis, Networks
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Foster, Colin – International Journal of Science and Mathematics Education, 2022
Confidence assessment (CA) involves students stating alongside each of their answers a confidence rating (e.g. 0 low to 10 high) to express how certain they are that their answer is correct. Each student's score is calculated as the sum of the confidence ratings on the items that they answered correctly, minus the sum of the confidence ratings on…
Descriptors: Mathematics Tests, Mathematics Education, Secondary School Students, Meta Analysis
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Chen, Xieling; Zou, Di; Cheng, Gary; Xie, Haoran; Su, Fan – Australasian Journal of Educational Technology, 2023
Despite accumulated evidence demonstrating the effectiveness of flipped language classrooms in higher education, there is no quantitative examination of the extant empirical studies to draw a general conclusion. Based on Bayesian methodologies and 26 effect sizes, this study quantitatively examines empirical studies that investigated flipped…
Descriptors: Flipped Classroom, Teaching Methods, Second Language Learning, Second Language Instruction
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
Zhang, Zhiyong; Jiang, Kaifeng; Liu, Haiyan; Oh, In-Sue – Grantee Submission, 2018
To answer the call of introducing more Bayesian techniques to organizational research (e.g., Kruschke, Aguinis, & Joo, 2012; Zyphur & Oswald, 2013), we propose a Bayesian approach for meta-analysis with power prior in this article. The primary purpose of this method is to allow meta-analytic researchers to control the contribution of each…
Descriptors: Bayesian Statistics, Meta Analysis, Correlation, Statistical Analysis
Polanin, Joshua R.; Hennessy, Emily A.; Tanner-Smith, Emily E. – Journal of Educational and Behavioral Statistics, 2017
Meta-analysis is a statistical technique that allows an analyst to synthesize effect sizes from multiple primary studies. To estimate meta-analysis models, the open-source statistical environment R is quickly becoming a popular choice. The meta-analytic community has contributed to this growth by developing numerous packages specific to…
Descriptors: Meta Analysis, Open Source Technology, Computer Software, Effect Size
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Karabatsos, George; Talbott, Elizabeth; Walker, Stephen G. – Research Synthesis Methods, 2015
In a meta-analysis, it is important to specify a model that adequately describes the effect-size distribution of the underlying population of studies. The conventional normal fixed-effect and normal random-effects models assume a normal effect-size population distribution, conditionally on parameters and covariates. For estimating the mean overall…
Descriptors: Bayesian Statistics, Meta Analysis, Prediction, Nonparametric Statistics
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Belland, Brian R.; Walker, Andrew E.; Kim, Nam Ju – Review of Educational Research, 2017
Computer-based scaffolding provides temporary support that enables students to participate in and become more proficient at complex skills like problem solving, argumentation, and evaluation. While meta-analyses have addressed between-subject differences on cognitive outcomes resulting from scaffolding, none has addressed within-subject gains.…
Descriptors: Bayesian Statistics, Meta Analysis, STEM Education, Computer Assisted Instruction
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Society for Research on Educational Effectiveness, 2013
One of the vexing problems in the analysis of SSD is in the assessment of the effect of intervention. Serial dependence notwithstanding, the linear model approach that has been advanced involves, in general, the fitting of regression lines (or curves) to the set of observations within each phase of the design and comparing the parameters of these…
Descriptors: Research Design, Effect Size, Intervention, Statistical Analysis
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Scammacca, Nancy K.; Roberts, Greg; Vaughn, Sharon; Stuebing, Karla K. – Journal of Learning Disabilities, 2015
This meta-analysis synthesizes the literature on interventions for struggling readers in Grades 4 through 12 published between 1980 and 2011. It updates Scammacca et al.'s analysis of studies published between 1980 and 2004. The combined corpus of 82 study-wise effect sizes was meta-analyzed to determine (a) the overall effectiveness of reading…
Descriptors: Meta Analysis, Intervention, Reading Difficulties, Elementary Secondary Education
Rindskopf, David; Shadish, William; Hedges, Larry – Society for Research on Educational Effectiveness, 2012
Data from single case designs (SCDs) have traditionally been analyzed by visual inspection rather than statistical models. As a consequence, effect sizes have been of little interest. Lately, some effect-size estimators have been proposed, but most are either (i) nonparametric, and/or (ii) based on an analogy incompatible with effect sizes from…
Descriptors: Intervention, Effect Size, Bayesian Statistics, Research Design
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Stevens, John R.; Taylor, Alan M. – Journal of Educational and Behavioral Statistics, 2009
Meta-analysis is a frequent tool among education and behavioral researchers to combine results from multiple experiments to arrive at a clear understanding of some effect of interest. One of the traditional assumptions in a meta-analysis is the independence of the effect sizes from the studies under consideration. This article presents a…
Descriptors: Meta Analysis, Vertical Organization, Effect Size, Computation
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