NotesFAQContact Us
Collection
Advanced
Search Tips
Showing all 4 results Save | Export
Peer reviewed Peer reviewed
Direct linkDirect link
Shaw, Mairead; Flake, Jessica K. – Educational Measurement: Issues and Practice, 2023
Clustered data structures are common in many areas of educational and psychological research (e.g., students clustered in schools, patients clustered by clinician). In the course of conducting research, questions are often administered to obtain scores reflecting latent constructs. Multilevel measurement models (MLMMs) allow for modeling…
Descriptors: Hierarchical Linear Modeling, Research Methodology, Data Analysis, Structural Equation Models
Peer reviewed Peer reviewed
Direct linkDirect link
Tara Slominski; Oluwatobi O. Odeleye; Jacob W. Wainman; Lisa L. Walsh; Karen Nylund-Gibson; Marsha Ing – CBE - Life Sciences Education, 2024
Mixture modeling is a latent variable (i.e., a variable that cannot be measured directly) approach to quantitatively represent unobserved subpopulations within an overall population. It includes a range of cross-sectional (such as latent class [LCA] or latent profile analysis) and longitudinal (such as latent transition analysis) analyses and is…
Descriptors: Educational Research, Multivariate Analysis, Research Methodology, Hierarchical Linear Modeling
Peer reviewed Peer reviewed
Direct linkDirect link
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
Peer reviewed Peer reviewed
PDF on ERIC Download full text
Schochet, Peter Z. – National Center for Education Evaluation and Regional Assistance, 2017
Design-based methods have recently been developed as a way to analyze data from impact evaluations of interventions, programs, and policies. The impact estimators are derived using the building blocks of experimental designs with minimal assumptions, and have good statistical properties. The methods apply to randomized controlled trials (RCTs) and…
Descriptors: Design, Randomized Controlled Trials, Quasiexperimental Design, Research Methodology