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Direct linkCheong, Yuk Fai; Kamata, Akihito – Applied Measurement in Education, 2013
In this article, we discuss and illustrate two centering and anchoring options available in differential item functioning (DIF) detection studies based on the hierarchical generalized linear and generalized linear mixed modeling frameworks. We compared and contrasted the assumptions of the two options, and examined the properties of their DIF…
Descriptors: Test Bias, Hierarchical Linear Modeling, Comparative Analysis, Test Items
Allen, Jeff – Applied Measurement in Education, 2017
Using a sample of schools testing annually in grades 9-11 with a vertically linked series of assessments, a latent growth curve model is used to model test scores with student intercepts and slopes nested within school. Missed assessments can occur because of student mobility, student dropout, absenteeism, and other reasons. Missing data…
Descriptors: Achievement Gains, Academic Achievement, Growth Models, Scores
Murphy, Daniel L.; Beretvas, S. Natasha – Applied Measurement in Education, 2015
This study examines the use of cross-classified random effects models (CCrem) and cross-classified multiple membership random effects models (CCMMrem) to model rater bias and estimate teacher effectiveness. Effect estimates are compared using CTT versus item response theory (IRT) scaling methods and three models (i.e., conventional multilevel…
Descriptors: Teacher Effectiveness, Comparative Analysis, Hierarchical Linear Modeling, Test Theory
