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Rashelle J. Musci; Joseph Kush; Elise T. Pas; Catherine P. Bradshaw – Grantee Submission, 2024
Given the increased focus of educational research on what works for whom and under what circumstances over the last decade, educational researchers are increasingly turning toward mixture models to identify heterogeneous subgroups among students. Such data are inherently nested, as students are nested within classrooms and schools. Yet there has…
Descriptors: Hierarchical Linear Modeling, Data Analysis, Nonparametric Statistics, Educational Research
Timothy Lycurgus; Daniel Almirall – Society for Research on Educational Effectiveness, 2024
Background: Education scientists are increasingly interested in constructing interventions that are adaptive over time to suit the evolving needs of students, classrooms, or schools. Such "adaptive interventions" (also referred to as dynamic treatment regimens or dynamic instructional regimes) determine which treatment should be offered…
Descriptors: Educational Research, Research Design, Randomized Controlled Trials, Intervention
Cox, Kyle; Kelcey, Benjamin – Educational and Psychological Measurement, 2023
Multilevel structural equation models (MSEMs) are well suited for educational research because they accommodate complex systems involving latent variables in multilevel settings. Estimation using Croon's bias-corrected factor score (BCFS) path estimation has recently been extended to MSEMs and demonstrated promise with limited sample sizes. This…
Descriptors: Structural Equation Models, Educational Research, Hierarchical Linear Modeling, Sample Size
Wei Li; Walter Leite; Jia Quan – Society for Research on Educational Effectiveness, 2023
Background: Multilevel randomized controlled trials (MRCTs) have been widely used to evaluate the causal effects of educational interventions. Traditionally, educational researchers and policymakers focused on the average treatment effects (ATE) of the intervention. Recently there has been an increasing interest in evaluating the heterogeneity of…
Descriptors: Artificial Intelligence, Identification, Hierarchical Linear Modeling, Randomized Controlled Trials
Aydin, Burak; Algina, James – Journal of Experimental Education, 2022
Decomposing variables into between and within components are often required in multilevel analysis. This method of decomposition should not ignore possible unreliability of an observed group mean (i.e., arithmetic mean) that is due to small cluster sizes and can lead to substantially biased estimates. Adjustment procedures that allow unbiased…
Descriptors: Hierarchical Linear Modeling, Prediction, Research Methodology, Educational Research
Yi Feng; Peter M. Steiner – Society for Research on Educational Effectiveness, 2022
Research Context: In educational research, "context effects" are often of inferential interest to researchers as well as of evaluative interest to policymakers. While student education outcomes likely depend on individual-level influences like individual academic achievement, school contexts may also make a difference. Such questions are…
Descriptors: Hierarchical Linear Modeling, Accuracy, Graphs, Educational Research
Avery H. Closser; Adam Sales; Anthony F. Botelho – Grantee Submission, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data on study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
Avery H. Closser; Adam Sales; Anthony F. Botelho – Educational Technology Research and Development, 2024
Emergent technologies present platforms for educational researchers to conduct randomized controlled trials (RCTs) and collect rich data to study students' performance, behavior, learning processes, and outcomes in authentic learning environments. As educational research increasingly uses methods and data collection from such platforms, it is…
Descriptors: Data Analysis, Educational Research, Randomized Controlled Trials, Sampling
Singh, Akansha; Uwimpuhwe, Germaine; Li, Mengchu; Einbeck, Jochen; Higgins, Steve; Kasim, Adetayo – International Journal of Research & Method in Education, 2022
In education, multisite trials involve randomization of pupils into intervention and comparison groups within schools. Most analytical models in multisite educational trials ignore that the impact of an intervention may be school dependent. This study investigates the impact of statistical models on the uncertainty associated with an effect size…
Descriptors: Randomized Controlled Trials, Effect Size, Hierarchical Linear Modeling, Least Squares Statistics
Lorah, Julie – Practical Assessment, Research & Evaluation, 2022
Applied educational researchers may be interested in exploring random slope effects in multilevel models, such as when examining individual growth trajectories with longitudinal data. Random slopes are effects for which the slope of an individual-level coefficient varies depending on group membership, however these effects can be difficult to…
Descriptors: Effect Size, Hierarchical Linear Modeling, Longitudinal Studies, Maximum Likelihood Statistics
Maria Vrikki; Leonidas Kyriakides; Andria Dimosthenous – Educational Research and Evaluation, 2024
The paper investigates the potential of using international large-scale assessment studies for conducting follow-up studies testing models of educational effectiveness. The impact of teacher factors coming from the "dynamic model of educational effectiveness" and the "dialogic education theory" on student literacy achievement…
Descriptors: Foreign Countries, Achievement Tests, Secondary School Students, International Assessment
Ann A. O'Connell; Nivedita Bhaktha; Jing Zhang – Society for Research on Educational Effectiveness, 2021
Background: Counts are familiar outcomes in education research settings, including those involving tests of interventions. Clustered data commonly occur in education research studies, given that data are often collected from students within classrooms or schools. There is a wide array of distributions and models that can be used for clustered…
Descriptors: Hierarchical Linear Modeling, Educational Research, Statistical Distributions, Multivariate Analysis
Ben Van Dusen; Heidi Cian; Jayson Nissen; Lucy Arellano; Adrienne D. Woods – Sociology of Education, 2024
This investigation examines the efficacy of multilevel analysis of individual heterogeneity and discriminatory accuracy (MAIHDA) over fixed-effects models when performing intersectional studies. The research questions are as follows: (1) What are typical strata representation rates and outcomes on physics research-based assessments? (2) To what…
Descriptors: Educational Research, Intersectionality, Critical Race Theory, STEM Education
Shen, Ting; Konstantopoulos, Spyros – Practical Assessment, Research & Evaluation, 2022
Large-scale assessment survey (LSAS) data are collected via complex sampling designs with special features (e.g., clustering and unequal probability of selection). Multilevel models have been utilized to account for clustering effects whereas the probability weighting approach (PWA) has been used to deal with design informativeness derived from…
Descriptors: Sampling, Weighted Scores, Hierarchical Linear Modeling, Educational Research
Headley, Marcia Gail; Plano Clark, Vicki L. – Journal of Mixed Methods Research, 2020
Many research problems in social science involve multilevel phenomena. However, discussions about multilevel research designs are limited in the mixed methods (MM) literature. Building on early writings in the field, this methodological discussion advances a refined definition of a multilevel MM research design. The refinement emerges from a…
Descriptors: Mixed Methods Research, Research Design, Hierarchical Linear Modeling, Educational Research