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Joo, Seang-Hwane; Wang, Yan; Ferron, John; Beretvas, S. Natasha; Moeyaert, Mariola; Van Den Noortgate, Wim – Journal of Educational and Behavioral Statistics, 2022
Multiple baseline (MB) designs are becoming more prevalent in educational and behavioral research, and as they do, there is growing interest in combining effect size estimates across studies. To further refine the meta-analytic methods of estimating the effect, this study developed and compared eight alternative methods of estimating intervention…
Descriptors: Meta Analysis, Effect Size, Computation, Statistical Analysis
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Jamshidi, Laleh; Declercq, Lies; Fernández-Castilla, Belén; Ferron, John M.; Moeyaert, Mariola; Beretvas, S. Natasha; Van den Noortgate, Wim – Journal of Experimental Education, 2021
Previous research found bias in the estimate of the overall fixed effects and variance components using multilevel meta-analyses of standardized single-case data. Therefore, we evaluate two adjustments in an attempt to reduce the bias and improve the statistical properties of the parameter estimates. The results confirm the existence of bias when…
Descriptors: Statistical Bias, Multivariate Analysis, Meta Analysis, Research Design
Fingerhut, Joelle; Xunyun, Xu; Moeyaert, Mariola – Grantee Submission, 2021
A variety of measures have been developed to quantify intervention effects for single-case experimental design studies. Within the family of non-overlap indices, the Tau-U measure is one of the most popular indices. There are several Tau-U variants, each one calculated differently. The appropriateness of each Tau-U variant depends upon the data…
Descriptors: Case Studies, Research Design, Research Tools, Decision Making
Moeyaert, Mariola; Yang, Panpan; Xu, Xinyun; Kim, Esther – Grantee Submission, 2021
Hierarchical linear modeling (HLM) has been recommended as a meta-analytic technique for the quantitative synthesis of single-case experimental design (SCED) studies. The HLM approach is flexible and can model a variety of different SCED data complexities, such as intervention heterogeneity. A major advantage of using HLM is that participant…
Descriptors: Meta Analysis, Case Studies, Research Design, Hierarchical Linear Modeling
Moeyaert, Mariola; Yang, Panpan – Grantee Submission, 2021
This study introduces an innovative meta-analytic approach, two-stage multilevel meta-analysis that considers the hierarchical structure of single-case experimental design (SCED) data. This approach is unique as it is suitable to include moderators at the intervention level, participant level, and study level, and is therefore especially…
Descriptors: Hierarchical Linear Modeling, Meta Analysis, Research Design, Case Studies
Peer reviewed Peer reviewed
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Asaro-Saddler, Kristie; Moeyaert, Mariola; Xu, Xinyun; Yerden, Xiaoyi – Exceptionality, 2021
In this study, we conducted a multilevel meta-analysis to determine whether the self-regulated strategy development (SRSD) approach to teaching writing to students with autism spectrum disorder (ASD) improves significantly the number of words written and overall quality of writing, whether the effects of SRSD were consistent or variable across…
Descriptors: Hierarchical Linear Modeling, Meta Analysis, Instructional Effectiveness, Self Control