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Bruno Arpino; Silvia Bacci; Leonardo Grilli; Raffaele Guetto; Carla Rampichini – Evaluation Review, 2025
We consider estimating the effect of a treatment on a given outcome measured on subjects tested both before and after treatment assignment in observational studies. A vast literature compares the competing approaches of modelling the post-test score conditionally on the pre-test score versus modelling the difference, namely, the gain score. Our…
Descriptors: Scores, Pretesting, Conditioning, Achievement Gains
Nimon, Kim – Career and Technical Education Research, 2012
Using state achievement data that are openly accessible, this paper demonstrates the application of hierarchical linear modeling within the context of career technical education research. Three prominent approaches to analyzing clustered data (i.e., modeling aggregated data, modeling disaggregated data, modeling hierarchical data) are discussed…
Descriptors: Vocational Education, Educational Research, Hierarchical Linear Modeling, Multivariate Analysis
Buhl, Sara J. – ProQuest LLC, 2012
This exploratory study examined the associations between teacher-student relationship ratings and characteristics of students and teachers. A sample of fifth grade teachers (N = 115) and their students (N = 2070) were studied. Hierarchical linear modeling was employed to explore the associations between variables while taking both individual…
Descriptors: Teacher Student Relationship, Student Characteristics, Teacher Characteristics, Hierarchical Linear Modeling
Vaughn, Brandon K. – Journal on School Educational Technology, 2008
This study considers the importance of contextual effects on the quality of assessments on item bias and differential item functioning (DIF) in measurement. Often, in educational studies, students are clustered in teachers or schools, and the clusters could impact psychometric issues yet are largely ignored by traditional item analyses. A…
Descriptors: Test Bias, Educational Assessment, Educational Quality, Context Effect