Researchers in career and technical education often ignore more effective ways of reporting and treating missing data and instead implement traditional, but ineffective, missing data methods (Gemici, Rojewski, & Lee, 2012). The recent methodological, and even the non-methodological, literature has increasingly emphasized the importance of…

A simulation study compared the performance of robust normal theory maximum likelihood (ML) and robust categorical least squares (cat-LS) methodology for estimating confirmatory factor analysis models with ordinal variables. Data were generated from 2 models with 2-7 categories, 4 sample sizes, 2 latent distributions, and 5 patterns of category…

Current value-added models for teacher accountability are better than models based only on student achievement, but they have their weakness. They are subject to systematic and random error, as are all measures, and there are concerns about the tests used for the measurements. However, value-added models are better than the alternatives at the…

The assessment procedures within Response to Intervention (RTI) models have begun to supplant the use of traditional, discrepancy-based frameworks for identifying students with specific learning disabilities (SLD). Many RTI proponents applaud this shift because of perceived shortcomings in utilizing discrepancy as an indicator of SLD. However,…

The use of value-added models in education research has expanded rapidly. These models allow researchers to explore how a wide variety of policies and measured school inputs affect the academic performance of students. An important question is whether such effects are sufficiently large to achieve various policy goals. Judging whether a change in…