This study looked at the effect of a number of factors such as the choice of analytical method, the handling method for missing data, sample size, and proportion of missing data, in order to evaluate the effect of missing data treatment on accuracy of estimation. In order to accomplish this a methodological approach involving simulated data was…

Nonlinear multilevel latent variable modeling has been suggested as an alternative to traditional hierarchical linear modeling to more properly handle measurement error and sampling error issues in contextual effects modeling. However, a nonlinear multilevel latent variable model requires significant computational effort because the estimation…

One of the major objectives of large-scale educational surveys is reporting trends in academic achievement. For this purpose, a substantial number of items are carried from one assessment cycle to the next. The linking process that places academic abilities measured in different assessments on a common scale is usually based on a concurrent…

This report summarizes research findings and implementation practices for teacher and principal value-added models (VAMs), as a first step in the Team Pennsylvania Foundation's (Team PA) pilot project to inform the development of a full, statewide model evaluation system. We have selected 21 studies that represent key issues and findings in the…

The paper initially describes the sources of uncertainty in National Assessment of Educational Progress (NAEP) data and standard errors. As NAEP sample sizes have increased, greater precision has been attained by the program. For this reason, exclusion effects are increasingly important. Two scenarios of revised NAEP results are presented (for New…