The present simulation study examined the statistical properties (namely, Type I error and statistical power) of various novel randomized single-case multiple-baseline designs and associated randomized-test analyses for comparing the A- to B-phase immediate abrupt outcome changes in two independent intervention conditions. It was found that with…

Multiple imputation (MI) is a popular method for handling missing data. In education research, it can be challenging to use MI because the data often have a clustered structure that need to be accommodated during MI. Although much research has considered applications of MI in hierarchical data, little is known about its use in cross-classified…

This dissertation comprises three papers that propose, discuss, and illustrate models to make improved inferences about research questions regarding student achievement in education. Addressing the types of questions common in educational research today requires three different "extensions" to traditional educational assessment: (1)…

The RMC Research Corporation evaluation model C1--the special regression model (SRM)--was evaluated through a series of computer simulations and compared with an alternative model, the norm referenced model (NRM). Using local data and national norm data to determine reasonable values for sample size and pretest posttest correlation parameters, the…

The RMC Model A (norm-referenced) for evaluation of Title I programs is based upon the equipercentile assumption--that students maintain their percentile rank over a one-year period, provided that no special instrucional intervention is introduced. The control group, essentially the sample used to standardize the achievement test, represents the…