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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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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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Westine, Carl D. – American Journal of Evaluation, 2016
Little is known empirically about intraclass correlations (ICCs) for multisite cluster randomized trial (MSCRT) designs, particularly in science education. In this study, ICCs suitable for science achievement studies using a three-level (students in schools in districts) MSCRT design that block on district are estimated and examined. Estimates of…
Descriptors: Efficiency, Evaluation Methods, Science Achievement, Correlation
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Westine, Carl D. – Society for Research on Educational Effectiveness, 2015
A cluster-randomized trial (CRT) relies on random assignment of intact clusters to treatment conditions, such as classrooms or schools (Raudenbush & Bryk, 2002). One specific type of CRT, a multi-site CRT (MSCRT), is commonly employed in educational research and evaluation studies (Spybrook & Raudenbush, 2009; Spybrook, 2014; Bloom,…
Descriptors: Correlation, Randomized Controlled Trials, Science Achievement, Cluster Grouping
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Cui, Ying; Mousavi, Amin – International Journal of Testing, 2015
The current study applied the person-fit statistic, l[subscript z], to data from a Canadian provincial achievement test to explore the usefulness of conducting person-fit analysis on large-scale assessments. Item parameter estimates were compared before and after the misfitting student responses, as identified by l[subscript z], were removed. The…
Descriptors: Measurement, Achievement Tests, Comparative Analysis, Test Items
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Adams, Curt M.; Forsyth, Patrick B.; Ware, Jordan; Mwavita, Mwarumba; Barnes, Laura L.; Khojasteb, Jam – Education Policy Analysis Archives, 2016
Oklahoma is one of 16 states electing to use an A-F letter grade as an indicator of school quality. On the surface, letter grades are an attractive policy instrument for school improvement; they are seemingly clear, simple, and easy to interpret. Evidence, however, on the use of letter grades as an instrument to rank and improve schools is scant…
Descriptors: Grading, Grades (Scholastic), Educational Quality, Educational Indicators
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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
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Feldman, Betsy J.; Rabe-Hesketh, Sophia – Journal of Educational and Behavioral Statistics, 2012
In longitudinal education studies, assuming that dropout and missing data occur completely at random is often unrealistic. When the probability of dropout depends on covariates and observed responses (called "missing at random" [MAR]), or on values of responses that are missing (called "informative" or "not missing at random" [NMAR]),…
Descriptors: Dropouts, Academic Achievement, Longitudinal Studies, Computation
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Johnson, Matthew S.; Jenkins, Frank – ETS Research Report Series, 2005
Large-scale educational assessments such as the National Assessment of Educational Progress (NAEP) sample examinees to whom an exam will be administered. In most situations the sampling design is not a simple random sample and must be accounted for in the estimating model. After reviewing the current operational estimation procedure for NAEP, this…
Descriptors: Bayesian Statistics, Hierarchical Linear Modeling, National Competency Tests, Sampling