QMRM Recent & Current Students
Fangxing Bai is advised by Dr. Ben Kelcey and interested in Quantitative Research Methodology with a focus on the design and analysis of cluster randomized trials, including multilevel modeling and estimation, optimal sample allocation and power analysis, and methods for fully/partially nested multisite clustered randomized trials. Fangxing presented his scholarly work at different conferences, including 2019 Mid-Western Educational Research Association Annual Meeting (MWERA), 2020 American Evaluation Association (AEA), and 2021 American Educational Research Association (AERA) conferences. Fangxing has been involved in numerous projects, and one of his work was published in Psychotherapy Research, which is the official journal of the Society for Psychotherapy Research (Impact Factor 2.98 – 2019). To learn more about Fangxing’s work, you may look into the following references:
Kelcey, B., Bai, F., & Xie, Y. (2020) Statistical power in partially nested designs probing multilevel mediation, Psychotherapy Research, 30(8), 1061-1074.
Bai, F., Kelcey, B., & Cox, K. (2020, October). Moderation with latent variables: A comparative analysis of estimators. Paper presented at the American Evaluation Association (AEA) Annual Conference, Virtual.
Bai, F., & Kelcey, B. (2019, October). Designing mediation studies with partially nested designs. Paper presented at the Mid-Western Educational Research Association (MWERA) Annual Meeting and Conference, Measurement & Research Methodology, Cincinnati, OH.
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. During his doctoral education here at the University of Cincinnati, he was advised by Dr. Ben Kelcey. Kyle’s research focuses on improving the feasibility of multilevel studies through design improvements and analytic advancements. This work is applicable across the social sciences as the methods accommodate natural hierarchical structures and complex theories, but Kyle is most interested in their application in educational settings. Specifically, Kyle has investigated statistical power in experimental multilevel mediation and moderation studies and is interested in improving the estimation of structural equation models when sample sizes are limited. To learn more about Kyle’s work, you may look into the following references:
Cox, K., & Kelcey, B. (in press). Statistical power for detecting moderation in partially nested designs. American Journal of Evaluation.
Kelcey, B., Cox, K., & Dong, N. (2021). Croon’s bias-corrected factor score path analysis for small- to moderate-sample multilevel structural equation models. Organizational Research Methods, 24, 55-77. https://doi.org/10.1177/1094428119879758
Cox, K. (2021, April). Croon’s Corrections for Estimating Single-Level Latent Interactions. Poster accepted at the American Educational Research Association Annual Meeting, Virtual/online.
Keanen McKinley is advised by Dr. Chris Swoboda and interested in understanding the application of quantitative methods and mixed methods research in the field of internationalization of higher education. His recent article assessed the quality of mixed methods research in the European student mobility literature, where “quality” was operationalized as the alignment between the rationales for using mixed methods research and the study design. As a doctoral candidate, Keanen is currently exploring missing data reporting practices in the internationalization literature, and he had the opportunity to present his preliminary findings at the 2021 Spring Research Conference. To learn more about Keanen’s work, you may look into the following references:
McKinley, K. M. (2021, March). Missing data reporting practices: Surveying the internationalization literature. Paper presented at the Spring Research Conference, University of Louisville, KY.
McKinley, K. M. (2019). Assessing mixed methods research quality in the European student mobility literature. Research in Comparative and International Education, 14(4), 433-449. https://doi.org/10.1177/1745499919889216.
Sinem Toraman is advised by Dr. Vicki L. Plano Clark and interested in mixed methods research applications and training. As an interdisciplinary methodologist, Sinem’s work focuses on the intersection of mixed methods research with different methodologies (e.g., social network analysis) and program evaluation. In her dissertation, she employs a novel mixed methods social network analysis approach that yielded a holistic understanding of research training and has implications for higher education institutions and policymakers to improve methodological teaching and training practices. In addition, Sinem’s dissertation has the potential to be considered as a framework for interdisciplinary researchers to investigate learning of emergent methods or methodologies that are becoming very popular among graduate students and researchers in various contexts. Sinem has worked on numerous research and program evaluation projects with scholars from the fields of education, health sciences, psychology, and social work. Among the many examples of Sinem’s work, here are the two studies on which she built her dissertation study:
Toraman, S., Cox, K., Plano Clark, V. L., & Dariotis, J. K. (2020). Graduate students’ current practices for writing a mixed methods research study abstract: An examination of doctoral dissertation and master’s thesis abstracts in the ProQuest Dissertations and Theses GlobalTM database. International Journal of Multiple Research Approaches, 12(1), 110-128. https://doi.org/10.29034/ijmra.v12n1a4
Toraman, S., & Plano Clark, V. L. (2020). Reflections about intersecting mixed methods research with social network analysis. In D. E. Froehlich, M. Rehm, & B. Rienties (Eds.), Mixed methods social network analysis: Theories and methodologies in learning and education (pp. 175 – 188). Routledge. https://doi.org/10.4324/9780429056826
Yanli Xie is advised by Dr. Ben Kelcey and interested in optimal sample size allocation under the partially nested clustered randomized trials that are widely used in educational, behavioral, and social science research. As a doctoral candidate, Yanli’s current research interests are driven by her involvement in different projects that focused on power analysis and partially nested design. These studies focus on power analysis for detecting mediation effect under three-level cluster-randomized trials. Yanli notes that working on these studies has helped her realize that sample planning, modeling, and analysis for partially nested trials are unique and important, but rarely appropriately applied in research. Her current work shows that inappropriate analytic methods yield biased estimates and erode the statistical power. Yanli’s work is important as the developed expressions will yield accurate power estimation and sample size calculation as well as help researchers design powerful and efficient partially nested trials. Yanli had a chance to present her work at the 2021 American Educational Research Association (AERA) conference. To learn more about Yanli’s work, you may look into the following references:
Kelcey, B., Xie, Y., Spybrook, J., Dong, N. (2020). Power and sample size determination for multilevel mediation in three-level cluster-randomized trials. Multivariate Behavioral Research, 1-18. https://doi.org/10.1080/00273171.2020.1738910
Kelcey, B., Bai, F., Xie, Y. (2020). Statistical power in partially nested designs probing multilevel mediation. Psychotherapy Research Journal, 30(8), 1061-1074. https://doi.org/10.1080/10503307.2020.1717012
Kelcey, B., Bai, F., Xie, Y., Cox, K. (2020). Croon-based estimation of small scale latent variable models integrating micro-macro and macro-micro effect. Testing Psychometrics Methodology in Applied Psychology, 27(3), 477-499.