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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
Moeyaert, Mariola; Yang, Panpan; Xu, Xinyun – Grantee Submission, 2021
This study investigated the power of two-level hierarchical linear modeling (HLM) to explain variability in intervention effectiveness between participants in context of single-case experimental design (SCED) research. HLM is a flexible technique that allows the inclusion of participant characteristics (e.g., age, gender, and disability types) as…
Descriptors: Hierarchical Linear Modeling, Intervention, Research Design, Participant Characteristics
Hitczenko, Marcin – Sociological Methods & Research, 2022
Researchers interested in studying the frequency of events or behaviors among a population must rely on count data provided by sampled individuals. Often, this involves a decision between live event counting, such as a behavioral diary, and recalled aggregate counts. Diaries are generally more accurate, but their greater cost and respondent burden…
Descriptors: Surveys, Social Science Research, Recall (Psychology), Diaries
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
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
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