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Min Liu · Associate Professor

  • Educational Psychology

Degrees (1)

Year
Degree
Major
Institute
2011
Ph.D
Measurement, Statistics, and Evaluation
University of Maryland, College Park

Book Chapters (1)

  • Hancock, G. R., & Liu, M. (2012). Bootstrapping Standard Errors and Data–Model Fit Statistics in Structural Equation Modeling. In R. H. Hoyle (Ed.), Handbook of Structural Equation Modeling. Guilford Press.

Journal Articles (12)

  • Cheng, B., Fan, A., & Liu, M. (2017). Trends, Reasons and Impacts of International Student Mobility: A Chinese Perspective. Frontiers of Education in China, 12(3).
  • Liu, M., Harbaugh, A. G., Harring, J., & Hancock, G. (2017). The effect of extreme response and non-extreme response styles on testing measurement invariance. Frontiers in Psychology, 8, 726.
  • Murphy, K. L., Liu, M., & Herzog, T. A. (2017). Confirmatory factor analysis and structural equation modeling of socio-cultural constructs among chamorro and non-chamorro micronesian betel nut chewers. Ethnicity & Health.
  • Wang, W.-L., Liu, M., & Lin, T.-I. (2017). Robust skew-t factor analysis models for handling missing data. Statistical Methods & Applications, 26(4), 649–672.
  • Zheng, D., Schmidt, M., Hu, Y., Liu, M., & Hsu, J. (2017). Eco-dialogical learning and translanguaging in open-ended 3D virtual learning environments. Australasian Journal of Educational Technology, 33(5), 107–122.
  • Galloway, J. C., Nigg, C., Liu, M., & Banna, J. (2015). Predictors of Change in Physical Activity and Fruit and Vegetable Intake in a Multiethnic Population in Hawaii at 6 and 12 Months Follow-up. International Journal of Applied Psychology, 5(2), 45–53.
  • Liu, M., & Lin, T.-I. (2015). Skew-normal factor analysis models with incomplete data. Journal of Applied Statistics, 42, 789–805.
  • Zheng, D., & Liu, M. (2015). An eco-dialogical study of second language learners' World of Warcraft (WoW) gameplay. Language Sciences, 48, 22–41.
  • Collins, C. S., & Liu, M. (2014). Greek Environments: An update on the effects of fraternities and sororities on health-related behaviors. Journal of College and Character, 15, 87–102.
  • Liu, M., & Hancock, G. R. (2014). Unrestricted mixture model for class identification in growth mixture modeling. Educational and Psychological Measurement, 74, 557–584.
  • Liu, M., & Lin, T.-I. (2014). A skew-normal mixture regression model. Educational and Psychological Measurement, 74, 139–162.
  • Liu, M., Hancock, G. R., & Harring, J. R. (2011). Using finite mixture modeling to deal with systematic measurement error: A case study. Journal of Modern Applied Statistical Methods, 10, 248–261.

Presentations (3)

  • Liu, M., & Lin, T. I. (2013). Mixture regression model with skew-normal errors. Presented at American Educational Research Association, San Francisco, CA.
  • Liu, M., & Hancock, G. R. (2012). Using joint criteria for class enumeration in growth and mixture modeling. Presented at American Educational Research Association Annual Meeting, Vancouver, British Columbia, Canada.
  • Liu, M., & Hancock, G. R. (2011). The impact of model selection on mixture model parameter estimate bias and variability: The case of growth mixture models. Presented at Annual meeting of the American Educational Research Association, New Orleans, LA.