Most enrollment management systems today use historical data to build rough forecasts of what percentage of students will likely accept an offer of enrollment based on historical acceptance rates. While this aggregate forecast method has its uses, we propose that building an enrollment model based on predicting an individual's likelihood of…

This article shows that the mean and covariance structure of the predetermined autoregressive latent trajectory (ALT) model are very flexible. As a result, the shape of the modeled growth curve can be quite different from what one might expect at first glance. This is illustrated with several numerical examples that show that, for example, a…

This "Practitioner's Guide to Growth Models," commissioned by the Technical Issues in Large-Scale Assessment (TILSA) and Accountability Systems & Reporting (ASR), collaboratives of the "Council of Chief State School Officers," describes different ways to calculate student academic growth and to make judgments about the…

The GGUM2004 computer program estimates parameters for a family of unidimensional unfolding item response theory (IRT) models. These unfolding IRT models predict higher item scores to the extent that a respondent is located close to an item on an underlying latent continuum. This prediction is often consistent with responses to traditional…

Describes using high school chemistry grades along with mathematics scores from the Scholastic Aptitude Test to predict college chemistry grades. Discusses rationale for the choice of predictive measures, the effect of teaching assistants, and supplemental study skills workshops on the grade received. (JM)

Traditional predictors have modest correlations with medical school grades and scores on the National Board of Medical Examiners examination for minority students. Noncognitive minority admissions variables are discussed including self-concept, realistic self-appraisal, understanding and dealing with racism, long-range goals, having a strong…