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Kim, Minjung; Hsu, Hsien-Yuan – Journal of Educational and Behavioral Statistics, 2019
Given the natural hierarchical structure in school-setting data, multilevel modeling (MLM) has been widely employed in education research using a number of different statistical software packages. The purpose of this article is to review a recent feature of Stat-JR, the statistical analysis assistants (SAAs) embedded in Stat-JR (Version 1.0.5),…
Descriptors: Hierarchical Linear Modeling, Statistical Analysis, Computer Software, Computer Software Evaluation
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Campione-Barr, Nicole; Lindell, Anna K.; Giron, Sonia E. – Developmental Psychology, 2020
The use of differences scores to assess agreement/disagreement has a long and contentious history. Laird (2020) notes, however, that developmentalists have been particularly resistant to discontinue the use of difference scores. One area of developmental science where difference scores are still in regular use is that of parental differential…
Descriptors: Educational Research, Hypothesis Testing, Differences, Scores
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Castellano, Katherine E.; Rabe-Hesketh, Sophia; Skrondal, Anders – Journal of Educational and Behavioral Statistics, 2014
Investigations of the effects of schools (or teachers) on student achievement focus on either (1) individual school effects, such as value-added analyses, or (2) school-type effects, such as comparisons of charter and public schools. Controlling for school composition by including student covariates is critical for valid estimation of either kind…
Descriptors: Hierarchical Linear Modeling, Context Effect, Economics, Educational Research
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Sun, Shuyan; Pan, Wei – International Journal of Research & Method in Education, 2014
As applications of multilevel modelling in educational research increase, researchers realize that multilevel data collected in many educational settings are often not purely nested. The most common multilevel non-nested data structure is one that involves student mobility in longitudinal studies. This article provides a methodological review of…
Descriptors: Statistical Analysis, Hierarchical Linear Modeling, Longitudinal Studies, Educational Research
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Jacob, Robin T.; Goddard, Roger D.; Kim, Eun Sook – Educational Evaluation and Policy Analysis, 2014
It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…
Descriptors: Academic Achievement, Data, Information Utilization, Educational Assessment
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Rhoads, Christopher – Journal of Research on Educational Effectiveness, 2016
Experimental evaluations that involve the educational system usually involve a hierarchical structure (students are nested within classrooms that are nested within schools, etc.). Concerns about contamination, where research subjects receive certain features of an intervention intended for subjects in a different experimental group, have often led…
Descriptors: Educational Experiments, Error of Measurement, Research Design, Statistical Analysis
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Azigwe, John Bosco – Journal of Education and Practice, 2016
International surveys of student achievement are becoming increasingly popular with governments around the world, as they try to measure the performance of their country's education system. The main reason for this trend is the shared opinion that countries will need to be able to compete in the "knowledge economy" to assure the economic…
Descriptors: Achievement Tests, Foreign Countries, International Assessment, Secondary School Students