This study seeks to further understanding of the STEM learning environment by 1) examining the extent to which mathematics and science achievement varies across students, teachers, schools, and districts, and 2) examining the extent to which student, teacher, school, and district characteristics that are found in state administrative databases can be used to explain this variation at each level. This work will support advances in research and evaluation methodologies that will enable researchers to design more rigorous and comprehensive evaluations of STEM interventions and improve the accuracy of statistical power calculations.
- Kelcey, B., Spybrook, J., Dong, N., & Bai, F. (in press). Experimental Power for Cross-Level Mediation in School-Randomized Studies of Teacher Development. Journal of Research on Educational Effectiveness.*
- Kelcey, B., Cox, K., & Dong, N. (in press). Croon’s Bias-Corrected Factor Score Path Analysis for Multilevel Structural Equation Models. Organizational Research Methods.*
- Kelcey, B., Spybrook, J., & Dong, N. (2019). Sample Size Planning in Cluster-randomized Studies of Multilevel Mediation. Prevention Science, 20, 407-418.*
- Kelcey, B., Hill, H., & Chin, M. (2019). Teacher Mathematical Knowledge, Instructional Quality, and Student Outcomes: A Multilevel Mediation Analysis. School Effectiveness & School Improvement.*