This study proposes a two-stage causal modeling with instrumental variables to mitigate selection bias, provide correct standard error estimates, and address nonnormal and missing data issues simultaneously. Bayesian methods are used for model estimation. Robust methods with Student's "t" distributions are used to account for nonnormal…

Recent methods to improve generalizations from nonrandom samples typically invoke assumptions such as the strong ignorability of sample selection, which is challenging to meet in practice. Although researchers acknowledge the difficulty in meeting this assumption, point estimates are still provided and used without considering alternative…

Memory plays a profound role in explaining language development, academic learning, and learning disabilities. Even though there is a large body of research on language development, literacy skills, other academic skills, and intellectual characteristics of children with hearing loss, there is no holistic study on their memory processes.…

Some form of a short interrupted time series (ITS) is often used to evaluate state and national programs. An ITS design with a single treatment group assumes that the pretest functional form can be validly estimated and extrapolated into the postintervention period where it provides a valid counterfactual. This assumption is problematic. Ambiguous…

Background: The relation between academic self-concept and achievement has been examined in a large number of studies. The majority of these studies have found evidence for a reciprocal effects model. However, there is an ongoing debate on how students' achievement should be measured and whether the type of achievement indicator (grades, tests,…

An analytical approach was employed to compare sensitivity of causal effect estimates with different assumptions on treatment noncompliance and non-response behaviors. The core of this approach is to fully clarify bias mechanisms of considered models and to connect these models based on common parameters. Focusing on intention-to-treat analysis,…

In this study, we examine grade-level growth rates for general education students and students with learning disabilities in grades two to six. In conducting the study, we demonstrate how schools, districts, and state educational agencies can use a combination of Curriculum-Based Measurement and Hierarchical Linear Modeling (HLM) methods to…

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…