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Direct linkTara 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
Paul Thompson; Kaydee Owen; Richard P. Hastings – International Journal of Research & Method in Education, 2024
Traditionally, cluster randomized controlled trials are analyzed with the average intervention effect of interest. However, in populations that contain higher degrees of heterogeneity or variation may differ across different values of a covariate, which may not be optimal. Within education and social science contexts, exploring the variation in…
Descriptors: Randomized Controlled Trials, Intervention, Mathematics Education, Mathematics Skills
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
