This paper discusses the limitations of Classical Test Theory, the purpose of Item Response Theory/Latent Trait Measurement models, and the step-by-step calculations in the Rasch measurement model. The paper explains how Item Response Theory (IRT) transforms person abilities and item difficulties into the same metric for test-independent and…

Applies neural network methods for forecasting 1991-95 per-pupil expenditures in U.S. public elementary and secondary schools. Forecasting models included the National Center for Education Statistics' multivariate regression model and three neural architectures. Regarding prediction accuracy, neural network results were comparable or superior to…

The problem of forecasting monthly demands for library network services is considered in terms of using forecasts as inputs to policy analysis models, and in terms of using forecasts to aid in the making of budgeting and staffing decisions. Box-Jenkins time-series methodology, adaptive filtering, and regression approaches are examined and compared…

The development of the error prone model (EPM) for the 1984-1985 student financial aid validation criteria for Pell Grant recipient selection is discussed, based on a comparison of the 1983-1984 EPM criteria and a newly estimated EPM. Procedures/assumptions on which the new EPM was based include: a sample of 1982-1983 Pell Grant recipients…

The development of a number of error-prone models to select Pell Grant recipients for validation is discussed. The 1983-1984 Pell Grant validation strategy consists of a two-stage approach: selection using Pre-Established Criteria (PEC) followed by selection using Error Prone Modeling (EPM). The database used for model development consists of a…