This is an application of contemporary multilevel regression modeling to the prediction of academic performances of 1st-year college students. At a first level of analysis, the data come from N greater than 16,000 students who were college freshman in 1994-1995 and who were also participants in high-level college athletics. At a second level of…

In the social sciences, latent traits often have a hierarchical structure, and data can be sampled from multiple levels. Both hierarchical latent traits and multilevel data can occur simultaneously. In this study, we developed a general class of item response theory models to accommodate both hierarchical latent traits and multilevel data. The…

Presented at the quarterly meeting of the New York Area SAS Users-Group in December 2008. In virtually any research context, there is likely to be opportunity to apply mixed-models--of which repeated-measures, multilevel, hierarchical and random- and fixed-effect models are specific types-- that improve upon their traditional linear or generalized…