Kyle Cox

photo of Kyle Cox
Educational Leadership
Assistant Professor

Kyle Cox is an assistant professor of educational research, measurement, and evaluation at University of North Carolina at Charlotte where he teaches graduate level statistics and research methods courses.  His research focuses on improving the feasibility of multilevel studies through design improvements and analytic advancements.  This work is particularly suitable for educational research as it accommodates the hierarchical structures and complex theories present in educational settings.  Specifically, Kyle has investigated statistical power in experimental multilevel mediation studies and is interested in the estimation of multilevel structural equation models.  Prior to joining UNC Charlotte in 2019, Kyle earned his doctorate in quantitative research methodology at the University of Cincinnati after nearly a decade of teaching 6th grade math.

EDUCATION

Ph.D.- University of Cincinnati, 2019, Educational Studies: Quantitative Research Methods
M.A.- University of Cincinnati, 2012, Educational Studies: Quantitative Research Methods
B.S.- Miami University, 2005, Education

TEACHING

Teaching Advanced Statistics
Research Methods

RESEARCH

Research Interests/Areas of Expertise
Structural Equation Modeling
Multilevel Modeling
Mediation
Experimental Design
Mathematics Education

AWARDS

University of Cincinnati Research Council Graduate Student Stipend and Research Cost Award for Faculty-Student Collaboration
2016 CADRE STEM Fellowship
Finalist for Top Proposal to the 2016 American Educational Research Association Annual Meeting: Division D In-Progress Research Gala
2015 Project Excellence Award for Teaching

 

Selected Publications
Cox, K., & Kelcey, B. (2019). Optimal Design of Cluster- and Multisite-Randomized Studies Using Fallible Outcome Measures. Evaluation Review.
Cox, K., & Kelcey, B. (2019). Optimal sample allocation in group-randomized mediation studies with a group-level mediator. The Journal of Experimental Education.
Kelcey, B., Cox, K., & Dong, N. (2019). Croon’s Bias-Corrected Factor Score Path Analysis for Small to Moderate Sample Multilevel Structural Equation Models. Organizational Research Methods.
 

Curriculum Vita