A large number of approaches have been proposed for estimating and testing the significance of indirect effects in mediation models. In this study, four sets of Monte Carlo simulations involving full latent variable structural equation models were run in order to contrast the effectiveness of the currently popular bias-corrected bootstrapping…

Selection bias is problematic when evaluating the effects of postsecondary interventions on college students, and can lead to biased estimates of program effects. While instrumental variables can be used to account for endogeneity due to self-selection, current practice requires that all five assumptions of instrumental variables be met in order…

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 Comparing Options in Secondary Mathematics: Investigating Curriculum (COSMIC) project is a longitudinal study of student learning from two types of mathematics curricula: integrated and subject-specific. Previous large-scale research studies such as the National Assessment of Educational Progress (NAEP) indicate that numerous variables are…

In the social sciences, evaluating the effectiveness of a program or intervention often leads researchers to draw causal inferences from observational research designs. Bias in estimated causal effects becomes an obvious problem in such settings. This paper presents the Heckman Model as an approach sometimes applied to observational data for the…

Focuses on the fact that an educational treatment typically involves an intervention in a growth process. By modelling this process, expected growth for various treatment groups under control conditions may be estimated. Actual growth can be compared with projected growth to estimate the value-added by the program. A simple model is developed. (RC)

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 accuracy with which regression models estimate treatment effects is dependent upon a number of conditions. The stability of the regression line (a function of sample size and correlation between pretest and posttest) is said to be the most important of these conditions. The utility of regression models is proportional to the size of the…

Structural equation models reanalyzed data from the 1969 Westinghouse Head Start evaluation and extended the analysis to blacks and full-year programs. Results showed that the selection bias for summer program whites was absent for blacks and full-year program whites, and that Head Start helped the most disadvantaged children. (SLD)

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…