Date of Award

Fall 2021

Document Type

Open Access Dissertation



First Advisor

Christine DiStefano


School climate is a well-studied issue in educational research. However, surveys of school climate tend to be analyzed using item-centered as opposed to person-centered methods. The current study evaluated the 2018 South Carolina School Climate Survey using advanced applications of mixture modeling in an attempt to identify latent profiles at the student and school levels. The relatively new manual BCH 3-Step approach was applied given its usefulness in analyzing multilevel data with covariates and distal outcomes. However, its application to multilevel mixture models leaves room for advancement and prompted the adoption of an alternative analysis plan that included separate analyses for students and schools.

A latent profile analysis was conducted at the student level and resulted in the identification of six student profiles. At the school level, the manual BCH 3-Step process was applied, allowing for the incorporation of a covariate for school poverty level and distal outcomes related to academic achievement. Two profiles were identified at the school level, but because schools were also assigned to 'known classes' based on type (elementary, middle, high), a total of six profiles were created and analyzed in relation to the covariate and distal outcomes. A discussion of the results and methodological challenges associated with this study follows alongside considerations about how school climate can and should be analyzed, interpreted, and applied from both methodological and policy perspectives.