Skip to Main Content

Yan Wang


image of Yan Wang
Yan Wang, Ph.D.Assistant Professor
  • College
    College of Fine Arts, Humanities and Social Sciences
  • Department
    Psychology
  • Phone
    (978) 934-3912
  • Office
    Health and Social Sciences Building - 389
  • Email

Research Interests

Structural equation modeling, multilevel modeling, Bayesian analysis, finite mixture modeling, propensity score analysis, and substantive issues in psychology & education (e.g., resilience, depression, student retention).

Education

  • Ph D: Measurement & Research, (2018), University of South Florida - Tampa, FL
    Supporting Area: Educational Psychology
    Dissertation/Thesis Title: Covariates in factor mixture modeling: Investigating measurement invariance across unobserved groups
  • MA: Curriculum and Instruction, (2013), Boston College - Boston, MA
  • BA: English Literature, (2011), Xiamen University - Xiamen, China
  • BS: Economics, (2011), Xiamen University - Xiamen, China

Selected Awards and Honors

  • Leslie C. Robbins Dean’s Excellence Award (2016) - University of South Florida
  • Conference Presentation Travel Grant (2015) - SouthEast SAS Users Group (SESUG)
  • University Graduate Fellowship Award (2013) - University of South Florida
  • Dean’s Scholarship (2011) - Boston College
  • National Scholarship (2008) - Xiamen University

Selected Publications

  • Kim, E., Wang, Y. (2018). Investigating sources of heterogeneity with 3-step multilevel factor mixture modeling: Beyond testing measurement invariance in cross-national studies. (Advance online publication:). Structural Equation Modeling: A Multidisciplinary Journal.
  • Wang, Y., Kim, E., Dedrick, R., Ferron, J., Tan, T. (2017). A multilevel bifactor approach to construct validation of the mixed-format Students Confident in Mathematics Scale (78:2 pp. 253-271). Educational and Psychological Measurement
  • Tan, T., Wang, Y., Ruggerio, A. (2017). Childhood adversity and children's academic functioning: Role of parenting stress and neighborhood support (26:10 pp. 2742-2752). Journal of Child and Family Studies
  • Kim, E., Wang, Y. (2017). Class enumeration and parameter recovery of growth mixture modeling and second-order growth mixture modeling in the presence of measurement noninvariance. Frontiers in Psychology, 8(1499).
  • Wang, Y., Rodriguez de Gil, P., Chen, Y., Kromrey, J., Kim, E., Nguyen, D., Pham, T., Romano, J. (2017). Comparing the performance of approaches for testing the Homogeneity of Variance assumption in one-factor ANOVA models. Educational and Psychological Measurement, 77(2) 305-329.
  • Wang, Y., Kim, E. (2017). Evaluating model fit and structural coefficient bias: A Bayesian approach to multilevel bifactor model misspecification. Structural Equation Modeling: A Multidisciplinary Journal, 24(5) 699-713.
  • Kim, E., Cao, C., Wang, Y., Nguyen, D. (2017). Measurement invariance testing with many groups: A comparison of five approaches. Structural Equation Modeling: A Multidisciplinary Journal, 24(4) 524-544.
  • St. John Walsh, A., Wesley, K., Tan, S., Lynn, C., Wang, Y., O'Leary, K. (2017). Screening for depression among youth with HIV in an integrated care setting. AIDS Care, 29(7) 851-857.
  • Kim, E., Joo, S., Lee, P., Wang, Y., Stark, S. (2016). Measurement invariance testing across between-level latent classes using multilevel factor mixture modeling (23:6 pp. 870-887). Structural Equation Modeling: A Multidisciplinary Journal