Lijuan (Peggy) Wang

Lijuan (Peggy) Wang

Associate Professor

Ph.D., University of Virginia 

  • Quantitative

(574) 631-7243

111 Haggar Hall

Notre Dame, IN 46556

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The areas of longitudinal data analysis, multilevel modeling, and structural equation modeling.


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.

Recent Publications

(*student author)

*Planalp. E. M., *Du, H., Braungart-Rieker, J. M., & Wang, L.  (accepted). Growth curve modeling to studying change: A comparison of approaches using longitudinal dyadic data with distinguishable dyads. Structural Equation Modeling.

*Zhang, Q. & Wang, L. (accepted). Moderation Analysis with Missing Data in the Predictors. Psychological Methods.

Wang, L. & *Anderson, S. F. (in press). A review of intensive longitudinal methods: An introduction to diary and experience sampling research.Journal of Educational and Behavioral Statistics.

*Du, H.  & Wang, L. (in press). A Bayesian power analysis procedure considering uncertainty in effect size estimates from a meta-analysis.Multivariate Behavioral Research.

Narvaez, D., Wang, L., & Cheng, A. (in press). Evolved Developmental Niche History: Relation to adult psychopathology and morality. Applied Developmental Science.

Deng, L., Wang, L., & Zhao, Y. (2016). How creativity was affected by environmental factors and individual characteristics: A cross-cultural comparison perspective. Creativity Research Journal28 (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 Modeling22(3), 383-400. 

Wang, L. & Preacher, K. J. (2015). Moderated mediation analysis using Bayesian methods. Structural Equation Modeling22(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.

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.

*Zhang, Q. & Wang, L. (2014). Aggregating and testing intra-individual correlations: methods and comparisons. Multivariate Behavioral Research49(2), 130-148.