Lijuan (Peggy) Wang
Ph.D., University of Virginia
Corbett Family Hall
Notre Dame, IN 46556
The areas of longitudinal data analysis, multilevel modeling, and structural equation modeling.
Professor Wang is open to mentoring graduate students in the fall
Lijuan Wang's research interests are in the areas of longitudinal data analysis (e.g., methods and models for studying intra-individual change, variability, and relations, and inter-individual differences in them), multilevel modeling (e.g., dyadic data analysis), structural equation modeling (e.g., mediation analysis), and study design issues (e.g., sample size determination). She is also interested in measurement issues related to longitudinal research. Substantively, she is interested in applying quantitative methods in developmental, family, health, and educational research.
Wang, L., & *Yang, M. (In press). On interindividual differences in intraindividual changes. In E. Ferrer, S. M. Boker, & K. J. Grimm (Eds.), Advances in Longitudinal Models for Multivariate Psychology. New York: Taylor & Francis.
Wang, L., *Yang, M., & *Liu, X. (2018). The impact of over-simplifying the between-subject covariance structure on inferences of fixed effects in modeling nested data. Structural Equation Modeling. https://doi.org/10.1080/10705511.2018.1489725
*Blaxon, J., Bergeman, C. S., & Wang, L. (2018). Daily stress reactivity across the lifespan: Longitudinal and cross-sectional effects of age. Journal of Gerontology: Psychological Sciences. doi: 10.1093/geronb/gby046
*Du, H., & Wang, L. (2018) Reliabilities of intraindividual variability indicators with autocorrelated longitudinal data: Implications for longitudinal study designs. Multivariate Behavioral Research. https://doi.org/10.1080/00273171.2018.1457939
*Joiner, R., Bergeman, C. S., & Wang, L. (2018). Affective experience across the adult lifespan: An accelerated longitudinal design. Psychology and Aging, 33(3), 399-412.
*Hornburg, C., Wang, L., & McNeil, N. (2018). Comparing meta-analysis and individual person data analysis using raw data on children’s understanding of equivalence. Child Development (the 2018 meta-analysis and individual participant data analysis special issue). DOI: 10.1111/cdev.13058.
Park, I. J. K., *Du, H., Wang, L., Williams, D. R., & Alegría, M. (2018). Racial/ethnic discrimination and mental health in Mexican-origin youths and their parents: Testing the “linked lives” hypothesis. Journal of Adolescent Health, 62, 480-487.
Park, I. J. K., Wang, L., Williams, D. R., & Alegria, M. (2018). Coping With Racism: Moderators of the Discrimination-Adjustment Link Among Mexican-Origin Adolescents. Child Development, 89, e293-e310.
*Zhang, Q., Wang, L., & Bergeman, C. S. (2017). Multilevel autoregressive mediation models: Specification, estimation, and applications. Psychological Methods, 22 (4), 649 - 666.
*Du, H., Liu, F., & Wang L. (2017). A Bayesian "fill in" method for correcting or publication bias in meta-analysis. Psychological Methods, 22 (4), 799 -817.
*Zhang, Q., & Wang, L. (2017). Moderation analysis with missing data in the predictors. Psychological Methods, 22 (4), 649 - 666.
Park, I. J. K., Wang, L., Williams, D. R., & Alegria, M. (2017). Does anger regulation mediate the discrimination-mental health link among Mexican-origin adolescents? A longitudinal mediation analysis using multilevel modeling. Developmental Psychology, 53(2), 340-352.
*Du, H., & Wang L. (2017). Investigating reliabilities of intraindividual variability indicators with autocorrelated longitudinal data. Multivariate Behavioral Research, 52 (1), 120-121.
*Planalp. E. M., *Du, H., Braungart-Rieker, J. M., & Wang, L. (2017). Growth curve modeling to studying change: A comparison of approaches using longitudinal dyadic data with distinguishable dyads. Structural Equation Modeling, 24(1), 129-147.
Wang, L., & *Anderson, S. F. (2016). A review of intensive longitudinal methods: An introduction to diary and experience sampling research. Journal of Educational and Behavioral Statistics, 41(6), 653-658.
*Du, H., & Wang, L. (2016). A Bayesian power analysis procedure considering uncertainty in effect size estimates from a meta-analysis. Multivariate Behavioral Research, 51(5), 589-605.
Narvaez, D., Wang, L., & Cheng, A. (2016). Evolved Developmental Niche History: Relation to adult psychopathology and morality. Applied Developmental Science, 4, 294-309.
Deng, L., Wang, L., & Zhao, Y. (2016). How creativity was affected by environmental factors and individual characteristics: A cross-cultural comparison perspective. Creativity Research Journal. 28 (3), 1-10.
*Du, H., & Wang, L. (2016). The impact of the number of dyads on estimation of dyadic data analysis using multilevel modeling. Methodology, 12, 21-31.
*Nuttall, A. K., Valentino, K., Wang, L., Lefever, J. B., & Borkowski, J. G. (2015). Maternal history of parentification and maternal warm responsiveness across the transition to parenthood: The mediating role of maternal knowledge of infant development. Journal of Family Psychology, 29(6), 863-872.
*Ke, Z., & Wang, L. (2015). Detecting individual differences in change: Methods and comparisons. Structural Equation Modeling, 22(3), 383-400.
Wang, L., & Preacher, K. J. (2015). Moderated mediation analysis using Bayesian methods. Structural Equation Modeling, 22(2), 249-263.
*Yang, M., Wang, L., & Maxwell, S. E. (2015). Bias in longitudinal data analysis with missing data using typical linear mixed-effects modeling and pattern-mixture approach: an analytical illustration. British Journal of Mathematical and Statistical Psychology, 68(2), 246-267.
*Zhang, Q., & Wang, L. (2015). Evaluating methods for moderation analysis with missing data in the predictors. Multivariate Behavioral Research, 50(1), 144-145.
Wang, L., & Maxwell, S. E. (2015). On disaggregating between-person and within-person effects with longitudinal data using multilevel models. Psychological Methods, 20(1), 63-83.