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Cao, Chunhua; Kim, Eun Sook; Chen, Yi-Hsin; Ferron, John; Stark, Stephen – Educational and Psychological Measurement, 2019
In multilevel multiple-indicator multiple-cause (MIMIC) models, covariates can interact at the within level, at the between level, or across levels. This study examines the performance of multilevel MIMIC models in estimating and detecting the interaction effect of two covariates through a simulation and provides an empirical demonstration of…
Descriptors: Hierarchical Linear Modeling, Structural Equation Models, Computation, Identification
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Sideridis, Georgios D. – Educational and Psychological Measurement, 2016
The purpose of the present studies was to test the hypothesis that the psychometric characteristics of ability scales may be significantly distorted if one accounts for emotional factors during test taking. Specifically, the present studies evaluate the effects of anxiety and motivation on the item difficulties of the Rasch model. In Study 1, the…
Descriptors: Learning Disabilities, Test Validity, Measures (Individuals), Hierarchical Linear Modeling
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Hecht, Martin; Weirich, Sebastian; Siegle, Thilo; Frey, Andreas – Educational and Psychological Measurement, 2015
The selection of an appropriate booklet design is an important element of large-scale assessments of student achievement. Two design properties that are typically optimized are the "balance" with respect to the positions the items are presented and with respect to the mutual occurrence of pairs of items in the same booklet. The purpose…
Descriptors: Measurement, Computation, Test Format, Test Items
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Albano, Anthony D.; Rodriguez, Michael C. – Educational and Psychological Measurement, 2013
Although a substantial amount of research has been conducted on differential item functioning in testing, studies have focused on detecting differential item functioning rather than on explaining how or why it may occur. Some recent work has explored sources of differential functioning using explanatory and multilevel item response models. This…
Descriptors: Test Bias, Hierarchical Linear Modeling, Gender Differences, Educational Opportunities
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Timmermans, Anneke C.; Snijders, Tom A. B.; Bosker, Roel J. – Educational and Psychological Measurement, 2013
In traditional studies on value-added indicators of educational effectiveness, students are usually treated as belonging to those schools where they took their final examination. However, in practice, students sometimes attend multiple schools and therefore it is questionable whether this assumption of belonging to the last school they attended…
Descriptors: School Effectiveness, Student Mobility, Elementary Schools, Secondary Schools
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Wang, Qiu; Diemer, Matthew A.; Maier, Kimberly S. – Educational and Psychological Measurement, 2013
This study integrated Bayesian hierarchical modeling and receiver operating characteristic analysis (BROCA) to evaluate how interest strength (IS) and interest differentiation (ID) predicted low–socioeconomic status (SES) youth's interest-major congruence (IMC). Using large-scale Kuder Career Search online-assessment data, this study fit three…
Descriptors: Bayesian Statistics, Socioeconomic Status, Student Interests, Gender Differences
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Shaw, Emily J.; Marini, Jessica P.; Mattern, Krista D. – Educational and Psychological Measurement, 2013
The current study evaluated the relationship between various operationalizations of the Advanced Placement[R] (AP) exam and course information with first-year grade point average (FYGPA) in college to better understand the role of AP in college admission decisions. In particular, the incremental validity of the different AP variables, above…
Descriptors: Advanced Placement Programs, Grade Point Average, College Freshmen, College Admission