Multilevel Modeling and Practice-Based Research

Multilevel IRT Modeling in Practice with the Package mlirt

Variance component models are generally accepted for the analysis of hierarchical structured data. A shortcoming is that outcome variables are still treated as measured without an error. Unreliable variables produce biases in the estimates of the other model parameters. The variability of the relationships across groups and the group-effects on individuals’ outcomes differ substantially when ta...

Rigor and Practice-based Research

Rigor is one of the cornerstones of high-quality academic research. For example, the UK Research Assessment Exercise 2008 (RAE) describes the highest grade of research as possessing " quality that is world-leading in terms of originality, significance, and rigour. " 1 This paper addresses the criterion of rigor in the context of so-called practice-based research in design. It is the autho...

Multilevel Regression and Multilevel Structural Equation Modeling

Multilevel modeling in general concerns models for relationships between variables defined at different levels of a hierarchical data set, which is often viewed as a multistage sample from a hierarchically structured population. Common applications are individuals within groups, repeated measures within individuals, longitudinal modeling, and cluster randomized trials. This chapter treats the m...

Practice based research

A Reflection on Research, Theory, Evidence-based Practice, and Quality Improvement