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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
Moranski, Kara; Ziegler, Nicole – Language Learning, 2021
Multisite research (MSR) offers the key advantages of greater statistical power and external validity via larger and more diverse participant pools. In second language acquisition (SLA) research, recent developments in meta-analysis have created a robust foundation for MSR. Although logistical and financial obstacles can complicate expansion…
Descriptors: Validity, Language Research, Second Language Learning, Meta Analysis
Lyons, Gregory L. – ProQuest LLC, 2017
In contrast to Early Intensive Behavioral Intervention (EIBI), there are far fewer meta-analyses evaluating Naturalistic Developmental Behavioral Interventions (NDBIs) (Schreibman et al., 2015). Indeed, Pivotal Response Treatment (PRT)--a prominent NDBI--lacks meta-analytic studies. In the context of developing a line of research on the…
Descriptors: Meta Analysis, Young Children, Autism, Hierarchical Linear Modeling
Wang, Shin-Yi; Parrila, Rauno; Cui, Ying – Journal of Autism and Developmental Disorders, 2013
This meta-analysis used hierarchical linear modeling to examine 115 single-case studies with 343 participants that examined the effectiveness of social skills interventions for individuals with autism spectrum disorder (ASD). The average effect size of the included studies was 1.40 (SD = 0.43, 95% CL = 1.32-1.48, N = 115). In the further, several…
Descriptors: Meta Analysis, Hierarchical Linear Modeling, Case Studies, Pervasive Developmental Disorders