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Bianconcini, Silvia; Cagnone, Silvia – Journal of Educational and Behavioral Statistics, 2012
The evaluation of the formative process in the University system has been assuming an ever increasing importance in the European countries. Within this context, the analysis of student performance and capabilities plays a fundamental role. In this work, the authors propose a multivariate latent growth model for studying the performances of a…
Descriptors: Academic Achievement, College Students, Multivariate Analysis, Models
Shin, Yongyun; Raudenbush, Stephen W. – Journal of Educational and Behavioral Statistics, 2010
In organizational studies involving multiple levels, the association between a covariate and an outcome often differs at different levels of aggregation, giving rise to widespread interest in "contextual effects models." Such models partition the regression into within- and between-cluster components. The conventional approach uses each…
Descriptors: Academic Achievement, National Surveys, Computation, Inferences
Tekwe, Carmen D.; Carter, Randy L.; Ma, Chang-Xing; Algina, James; Lucas, Maurice E.; Roth, Jeffrey; Ariet, Mario; Fisher, Thomas; Resnick, Michael B. – Journal of Educational and Behavioral Statistics, 2004
Hierarchical Linear Models (HLM) have been used extensively for value-added analysis, adjusting for important student and school-level covariates such as socioeconomic status. A recently proposed alternative, the Layered Mixed Effects Model (LMEM) also analyzes learning gains, but ignores sociodemographic factors. Other features of LMEM, such as…
Descriptors: Accountability, Academic Achievement, Mathematical Models, Statistical Analysis