Clustered data structures are common in many areas of educational and psychological research (e.g., students clustered in schools, patients clustered by clinician). In the course of conducting research, questions are often administered to obtain scores reflecting latent constructs. Multilevel measurement models (MLMMs) allow for modeling…

Sophisticated analytic strategies have been proposed as viable methods to improve the quantification of student improvement and to assist educators in making treatment decisions. The performance of three categories of latent growth modeling techniques (linear, quadratic, and dual change) to capture growth in oral reading fluency in response to a…

In this ITEMS module, we frame the topic of scale reliability within a "confirmatory factor analysis" and "structural equation modeling" (SEM) context and address some of the limitations of Cronbach's a. This modeling approach has two major advantages: (1) it allows researchers to make explicit the relation between their items…

Structural equation modeling (SEM) is a versatile statistical modeling tool. Its estimation techniques, modeling capacities, and breadth of applications are expanding rapidly. This module introduces some common terminologies. General steps of SEM are discussed along with important considerations in each step. Simple examples are provided to…

This research investigates the relative importance of vocabulary and oral reading fluency as measurement dimensions of reading comprehension as the student passes from elementary to high school. Invariance of this model over grades 4 through 8 is tested using two independent student samples reading grade-level appropriate passages. Results from…