Lijuan (Peggy) Wang
Professor
- Office
- E436 Corbett Family Hall
Notre Dame, IN 46556 - Phone
- +1 574-631-7243
- lwang4@nd.edu
Research and teaching interests
(Intensive) longitudinal data analysis, mediation analysis, moderation analysis, multilevel modeling, structural equation modeling, and study designs
Biography
Dr. Lijuan Wang's research interests are in the areas of Bayesian modeling, cumulative data analysis, dyadic data analysis, (intensive) longitudinal data analysis, mediation analysis, moderation analysis, multilevel modeling, structural equation modeling, and study designs. Particularly, she is interested in developing methods for combinations of these areas such as studying mediation or moderation analytics from the longitudinal perspective and sample size planning for mediation and longitudinal studies. Substantively, she is interested in applying quantitative methods in clinical, developmental, education, family, and health research.
Education
Ph.D. from University of Virginia
Representative Publications
*Fang, Y., & Wang, L. (2024). Dynamic structural equation modeling with missing data: Data requirements for N and T. Structural Equation Modeling, 31(5), 891-908. doi: 10.1080/10705511.2023.2287967.
*Li, R., & Wang, L. (2024). Investigating weight constraint methods for modeling causal-formative indicators. Behavior Research Methods, 56(7), 6485-6497. doi: 10.3758/s13428-024-02365-9.
*Wilcox, K. T., & Wang, L. (2023). Modeling approaches for cross-sectional integrative data analysis: Evaluations and recommendations. Psychological Methods, 28(1), 242-261. doi: 10.1037/met0000397.
*Liu, X., & Wang, L. (2021). The impact of measurement error and omitting confounders on statistical inference of mediation effects and tools for sensitivity analysis. Psychological Methods, 26(3), 327-342. doi: 10.1037/met0000345.
*Liu, Q., & Wang, L. (2021). t-test and ANOVA for data with ceiling and/or floor effects. Behavior Research Methods, 53, 264-277. doi: 10.3758/s13428-020-01407-2.
Wang, L., & Zhang, Q. (2020). Investigating the impact of the time interval selection on autoregressive mediation modeling: Result interpretations, effect reporting, and temporal designs. Psychological Methods, 25(3), 271–291. doi: 10.1037/met0000235.
*Du, H., & Wang, L. (2018) Reliabilities of intraindividual variability indicators with autocorrelated longitudinal data: Implications for longitudinal study designs. Multivariate Behavioral Research, 53(4), 502-520. doi: 10.1080/00273171.2018.1457939.
Wang, L., Zhang, Q., Maxwell, S. E., & Bergeman, C. S. (2019). On standardizing within-person effects: Potential problems of global standardization. Multivariate Behavioral Research, 54(3), 382-403. doi: 10.1080/00273171.2018.1532280.
*Zhang, Q., & Wang, L. (2017). Moderation analysis with missing data in the predictors. Psychological Methods, 22(4), 649 - 666. doi: 10.1037/met0000104.
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. doi: 10.1037/met0000030.
Wang, L., & Preacher, K. J. (2015). Moderated mediation analysis using Bayesian methods. Structural Equation Modeling, 22(2), 249-263. doi: 10.1080/10705511.2014.935256.
Wang, L., Hamaker, E., & Bergeman, C. (2012). Investigating inter-individual differences in short-term intra-individual variability. Psychological Methods, 17(4), 567-581. doi: 10.1037/a0029317.
Wang, L., Zhang, Z., McArdle, J. J., & Salthouse, T. A. (2008). Investigating ceiling effects in longitudinal data analysis. Multivariate Behavioral Research, 43(3), 476-496. doi: 10.1080/00273170802285941.