EDUCATION
| Ph.D. | Educational Measurement and Research Methods | University of South Florida |
| M.A. | English Language and Literature | Shanghai International Studies University |
| B.A. | English/Language Arts, Teacher Education | Hunan Normal University |
AREAS OF EXPERTISE
Application of quantitative research methods
Answering research questions in education, psychology and other social sciences
RESEARCH INTERESTS
Structural equation modeling
Multilevel modeling
Mixture modeling
Bayesian estimation methods
HIGHLIGHTED PUBLICATIONS
- Cao, C, Wang, Y, & Kim, E. S. (in press). Multilevel Factor Mixture Modeling: A Tutorial of Multilevel Construct. Structural Equation Modeling: A Multidisciplinary Journal.
- Cao, C., *Lugu, B., & *Li, J. (2024). The sensitivity of Bayesian fit indices to structural misspecification in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal.
- Cao, C., & Liang, X. (2024). The Impact of Ignoring Cross-loadings on the Sensitivity of Fit Measures in Measurement Invariance Testing. Structural Equation Modeling: A Multidisciplinary Journal.
- Cao, C., Man, K., & *Ge, Y. (2023). Revisiting the impact of measurement quality on targeted structural fit indexes in structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal.
- Cao, C., & Liang, X. (2022). The impact of model size on the sensitivity of fit measures in measurement invariance testing. Structural Equation Modeling: A Multidisciplinary Journal.
- Cao, C., & Liang, X. (2022). Sensitivity of fit measures to the lack of measurement invariance in exploratory structural equation modeling. Structural Equation Modeling: A Multidisciplinary Journal.
PROFESSIONAL MEMBERSHIPS / ACTIVITIES
- Member of AERA, IMPS, ISDSA
- Reviewer for top-tier journals, such as Structural Equation Modeling: A Multidisciplinary Journal and Behavior Research Methods
BIOGRAPHY
Dr. Chunhua Cao a methodological scholar within the field of structural equation modeling (SEM), multilevel modeling, and Bayesian estimation. In the framework of SEM, one important issue about modeling in SEM is model fit evaluation. Her current and future research projects are all connected through a common focus on developing and assessing methods for evaluating SEM models within the context of education and social sciences. These efforts include research that focuses primarily on evaluating the sensitivity of fit measures to measurement noninvariance and model misspecification. The results from these research studies have important implications for applied researchers. She also collaborates with empirical researchers to apply statistical and measurement knowledge to real-world research.
Teaching philosophy and approach
Dr. Cao’s ultimate teaching goal is to help all her students to be well prepared for successfully applying the knowledge they have learnt to their own research and work. As a teacher, she attempts to help her students to be motivated, independent and successful learners. The conceptual understanding and application of the statistics methods is very important.