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…

Multilevel modeling (MLM) is frequently used to detect group differences, such as an intervention effect in a pre-test--post-test cluster-randomized design. Group differences on the post-test scores are detected by controlling for pre-test scores as a proxy variable for unobserved factors that predict future attributes. The pre-test and post-test…

Researchers have become increasingly interested in programs' main and interaction effects of two variables (A and B, e.g., two treatment variables or one treatment variable and one moderator) on outcomes. A challenge for estimating main and interaction effects is to eliminate selection bias across A-by-B groups. I introduce Rubin's causal model to…

To reduce the high incidence of cervical cancer among Latinas in the United States it is important to understand factors that predict screening behavior. The aim of this study was to test the utility of theory of planned behavior in predicting cervical cancer screening among a group of Latinas. A sample of Latinas (N = 614) completed a baseline…

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)…

Multisite trials can clarify the average impact of a new program and the heterogeneity of impacts across sites. Unfortunately, in many applications, compliance with treatment assignment is imperfect. For these applications, we propose an instrumental variable (IV) model with person-specific and site-specific random coefficients. Site-specific IV…

Multiple uses of the same assessment may present challenges for both the design and use of an assessment. Little advice, however, has been given to assessment developers as to how to understand the phenomena of multiple assessment use and meet the challenges these present. Particularly problematic is the case in which an assessment is used for…

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…

The regression-discontinuity approach to evaluating educational programs is reviewed, and regression-discontinuity post-program mean differences under various conditions are discussed. The regression-discontinuity design is used to determine whether post-program differences exist between an experimental program and a control group. The difference…