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Vidotto, Davide; Vermunt, Jeroen K.; van Deun, Katrijn – Journal of Educational and Behavioral Statistics, 2018
With this article, we propose using a Bayesian multilevel latent class (BMLC; or mixture) model for the multiple imputation of nested categorical data. Unlike recently developed methods that can only pick up associations between pairs of variables, the multilevel mixture model we propose is flexible enough to automatically deal with complex…
Descriptors: Bayesian Statistics, Multivariate Analysis, Data, Hierarchical Linear Modeling
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Grund, Simon; Lüdtke, Oliver; Robitzsch, Alexander – Journal of Educational and Behavioral Statistics, 2018
Multiple imputation (MI) can be used to address missing data at Level 2 in multilevel research. In this article, we compare joint modeling (JM) and the fully conditional specification (FCS) of MI as well as different strategies for including auxiliary variables at Level 1 using either their manifest or their latent cluster means. We show with…
Descriptors: Statistical Analysis, Data, Comparative Analysis, Hierarchical Linear Modeling
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Hartley, Sigan L.; DaWalt, Leann Smith; Schultz, Haley M. – Journal of Autism and Developmental Disorders, 2017
We examined daily couple experiences in 174 couples who had a child with autism spectrum disorder (ASD) relative to 179 couples who had a child without disabilities and their same-day association with parent affect. Parents completed a 14-day daily diary in which they reported time with partner, partner support, partner closeness, and positive and…
Descriptors: Spouses, Interpersonal Relationship, Children, Autism
Hedges, Larry V.; Hedberg, Eric C. – Grantee Submission, 2013
Background: Cluster randomized experiments that assign intact groups such as schools or school districts to treatment conditions are increasingly common in educational research. Such experiments are inherently multilevel designs whose sensitivity (statistical power and precision of estimates) depends on the variance decomposition across levels.…
Descriptors: Correlation, Multivariate Analysis, Educational Experiments, Academic Achievement
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Pituch, Keenan A.; Whittaker, Tiffany A.; Chang, Wanchen – American Journal of Evaluation, 2016
Use of multivariate analysis (e.g., multivariate analysis of variance) is common when normally distributed outcomes are collected in intervention research. However, when mixed responses--a set of normal and binary outcomes--are collected, standard multivariate analyses are no longer suitable. While mixed responses are often obtained in…
Descriptors: Intervention, Multivariate Analysis, Mixed Methods Research, Models
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Ward, Carol; Gibbs, Benjamin G.; Buttars, Rilee; Gaither, Patricia Grace; Burraston, Bert – Journal of Education for Students Placed at Risk, 2015
This study examines math and English standardized test score progress of students who participated in the 21st century program across 2 years of involvement with a focus on the learning trajectories of limited English proficiency (LEP) students. We find that math and English scores are highly associated with the school and program type--even…
Descriptors: After School Programs, Limited English Speaking, Program Effectiveness, Mathematics Tests
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Woolf, Katherine; McManus, I. Chris; Potts, Henry W. W.; Dacre, Jane – British Journal of Educational Psychology, 2013
Background: UK-trained medical students and doctors from minority ethnic groups underperform academically. It is unclear why this problem exists, which makes it dif?cult to know how to address it. Aim: To investigate whether demographic and psychological factors mediate the relationship between ethnicity and ?nal examination scores. Sample: Two…
Descriptors: Foreign Countries, Medical Students, Cohort Analysis, Medical Schools
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Strand, Steve – Review of Education, 2016
Relatively little research has explored whether schools differ in their effectiveness for different group of pupils (e.g. by ethnicity, poverty or gender), for different curriculum subjects (e.g. English, mathematics or science) or over time (different cohorts). This paper uses multilevel modelling to analyse the national test results at age 7 and…
Descriptors: School Effectiveness, Hierarchical Linear Modeling, Children, Elementary School Students