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Henry H. Zink; Ethan R. Van Norman; David A. Klingbeil – Psychology in the Schools, 2024
Single-case design (SCD) is a quantitative experimental technique in which participants serve as their own control. The use of an effect size in SCD allows evaluation of outcomes as well as comparison of outcomes via meta-analyses. Characteristics of SCD research make the selection of an appropriate effect size complicated. Additionally, there are…
Descriptors: Research Design, Case Studies, Effect Size, Academic Ability
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Henry H. Zink; Ethan R. Van Norman; David A. Klingbeil – Grantee Submission, 2023
Single-case design (SCD) is a quantitative experimental technique in which participants serve as their own control. The use of an effect size in SCD allows evaluation of outcomes as well as comparison of outcomes via meta-analyses. Characteristics of SCD research make the selection of an appropriate effect size complicated. Additionally, there are…
Descriptors: Research Design, Case Studies, Effect Size, Academic Ability
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Jager, Nicolas W.; Newig, Jens; Challies, Edward; Kochskämper, Elisa; von Wehrden, Henrik – Research Synthesis Methods, 2022
Meta-analytical methods face particular challenges in research fields such as social and political research, where studies often rest primarily on qualitative and case study research. In such contexts, where research findings are less standardized and amenable to structured synthesis, the case survey method has been proposed as a means of data…
Descriptors: Social Sciences, Meta Analysis, Case Studies, Validity
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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
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
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McDaniel, Jena; Brady, Nancy C.; Warren, Steven F. – Journal of Autism and Developmental Disorders, 2022
We conducted a systematic review to identify randomized controlled trials (RCTs) and single case research design (SCRD) studies of children with autism spectrum disorder that evaluate the effectiveness of responsivity intervention techniques for improving prelinguistic and/or language outcomes. Mean effect sizes were moderate and large for RCTs…
Descriptors: Outcomes of Treatment, Response to Intervention, Child Language, Autism Spectrum Disorders
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Baek, Eunkyeng; Luo, Wen; Henri, Maria – Journal of Experimental Education, 2022
It is common to include multiple dependent variables (DVs) in single-case experimental design (SCED) meta-analyses. However, statistical issues associated with multiple DVs in the multilevel modeling approach (i.e., possible dependency of error, heterogeneous treatment effects, and heterogeneous error structures) have not been fully investigated.…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Comparative Analysis, Statistical Inference
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Aspiranti, Kathleen B.; McCallum, Elizabeth; Schmitt, Ara J. – Contemporary School Psychology, 2019
The taped problems (TP) intervention is a math fact fluency intervention designed to produce high rates of active and accurate academic responding. Multiple single-case design studies have examined the use of TP across grades of students, implementation group sizes, intervention settings, target math facts, total intervention time, application of…
Descriptors: Intervention, Mathematics Instruction, Case Studies, Reinforcement
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Ryo, Masahiro; Jeschke, Jonathan M.; Rillig, Matthias C.; Heger, Tina – Research Synthesis Methods, 2020
Research synthesis on simple yet general hypotheses and ideas is challenging in scientific disciplines studying highly context-dependent systems such as medical, social, and biological sciences. This study shows that machine learning, equation-free statistical modeling of artificial intelligence, is a promising synthesis tool for discovering novel…
Descriptors: Artificial Intelligence, Case Studies, Biology, Research Reports
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Vo, Tat-Thang; Porcher, Raphael; Chaimani, Anna; Vansteelandt, Stijn – Research Synthesis Methods, 2019
Case-mix heterogeneity across studies complicates meta-analyses. As a result of this, treatments that are equally effective on patient subgroups may appear to have different effectiveness on patient populations with different case mix. It is therefore important that meta-analyses be explicit for what patient population they describe the treatment…
Descriptors: Case Studies, Meta Analysis, Research Problems, Medical Research
Jamshidi, Laleh; Declercq, Lies; Fernández-Castilla, Belén; Ferron, John M.; Moeyaert, Mariola; Beretvas, S. Natasha; Van den Noortgate, Wim – Grantee Submission, 2020
The focus of the current study is on handling the dependence among multiple regression coefficients representing the treatment effects when meta-analyzing data from single-case experimental studies. We compare the results when applying three different multilevel meta-analytic models (i.e., a univariate multilevel model avoiding the dependence, a…
Descriptors: Multivariate Analysis, Hierarchical Linear Modeling, Meta Analysis, Regression (Statistics)
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Fougt, Simon Skov; Misfeldt, Morten; Shaffer, David Williamson – Journal of Interactive Learning Research, 2019
This study explores the concept of authenticity in education, which has been, over the last 25 years, a powerful metaphor for educational practice, particularly as a guiding principle for some technological innovations that support student learning. The concept of authenticity has a variety of meanings, although a dominant interpretation is that…
Descriptors: Authentic Learning, Experiential Learning, Computer Assisted Instruction, Class Activities
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Wiley, Jennifer L.; Wiley, Kristofor R.; Intolubbe-Chmil, Loren; Bhuyan, Devi; Acheson, Kris – Journal of Transformative Education, 2021
Transformative learning (TL) goals are becoming commonplace in higher education, continuing education, and other adult learning contexts; however, valid and reliable assessments of TL are not so common. This imbalance begs the development of assessment methods that allow for a deeper understanding of how, when, and why deep reshaping of self takes…
Descriptors: Evaluation Methods, Transformative Learning, Measures (Individuals), Values
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Pustejovsky, James E. – Grantee Submission, 2018
A wide variety of effect size indices have been proposed for quantifying the magnitude of treatment effects in single-case designs. Commonly used measures include parametric indices such as the standardized mean difference, as well as non-overlap measures such as the percentage of non-overlapping data, improvement rate difference, and non-overlap…
Descriptors: Effect Size, Measurement Techniques, Monte Carlo Methods, Observation
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