Summer 2019 Masters Candidate
"Assess Three-Level-Cross-Classified Model on LME4 Package"
The use of the hierarchical linear model is increasingly common in the medical and educational research. In education. the data structure requires more than an ordinary linear model in order to obtain a precise outcome. A leading example is the student's achievements in math while in elementary school. In this example, the test score is nested within both the teacher's and the student's characteristics and the student and the teacher are nested within the school's characteristics. Additionally, the student and the teacher are cross-classified. The three-level-cross-classified model explains the student's achievements based on teacher's effect on a student's characteristics and the school's characteristics. The research investigates the capability of the R package lme4 to fit the three-level-cross classified model.