Haiyan Liu - Publications

Journal Publications

32. Liu, H., Heo, I., Depaoli, S., & Ivanov, A. (2025) Parameter Recovery for Misspecified Latent Mediation Models in the Bayesian Framework, Structural Equation Modeling: A Multidisciplinary Journal Disciplinary Journal.

31. Heo, I., Depaoli, S., Jia, F., &, Liu, H. (2024) Bayesian Approach to Piecewise Growth Mixture Modeling: Issues and Applications in School Psychology, Journal of School Psychology

30. Liu, H., & Liu, R. (2024) Latent Variable Modeling of Social Networks with Directional Relations: An Exploration of Profile Similarity of Latent Factors. Structural Equation Modeling; A Multidisciplinary Journal. https://doi.org/10.1080/10705511.2024.2376329

29. Liu, H., Tsang, S., Wood, A., & Tong, X. (2024) Longitudinal Sentiment Analysis with Conversation Textual Data. Fudan Journal of the Humanities and Social Sciences. https://doi.org/10.1007/s40647-024-00417-0

28. Depaoli, S., Winter, S., & Liu, H. (2023) Under-Fitting and Over-Fitting: The Performance of Bayesian Model Selection and Fit Indices in SEM. Structural Equation Modeling: A Multidisciplinary Journal https://doi.org/10.1080/10705511.2023.2280952

27. Marvin, L., Liu, H., Depaoli, S. (2023). Using Bayesian Piecewise Growth Curve Models to Handle Complex Nonlinear Trajectories. Journal of Behavioral Data Science, 3(1), 1-33.

26. Liu, R., Heo, I., Liu, H., Shi, D., & Jiang, Z. (2023). Applying negative binomial distribution in diagnostic classification models for analyzing count data. Applied Psychological Measurement. (doi: 10.1177/01466216221124604)

25. Liu, R., Liu, H., Shi, D., & Jiang, Z. (2022) Diagnostic Classification Models for a Mixture of Ordered and Non-ordered Response Options in Rating Scales. Applied Psychological Measurement.

24. Liu, H., Qu, W., Zhang, Z., & Wu, H. (2022) A new Bayesian Structural Equation Modeling Approach with Priors on the Covariance Matrix Parameter. Journal of Behavioral Data Science.

23. Liu, H., Depaoli, S., & Marvin, L. (2022) Understanding the Deviance Information Criterion for SEM: Cautions in Prior Specification

22. Koenig, C., Depaoli, S., Liu, H., & Van De Schoot, R. (2021) Moving Beyond Non-Informative Prior Distributions-Achieving the Full Potential of Bayesian Methods for Psychological Research Frontiers in Psychology

21. Liu, R, Liu, H., Shi, D., & Jiang, Z. (2021). Applying Poisson Distribution in Diagnostic Classification Models: An Exploratory Example. Educational and Psychological Measurement. https://doi.org/10.1177/00131644211017961

20. Depaoli, S., Liu, H., & Marvin, L.* (2021). How parameterization impacts the performance of Bayesian structural equation modeling: An exploration of priors. Structural Equation Modeling: A Multidisciplinary Journal

19. Liu, H., & Zhang, Z. (2021). Birds of a feather flock together and Opposites attract: The nonlinear relationship between personality and friendship. Journal of Behavioral Data Science, 1(1), 34–52. https://doi.org/10.35566/jbds/v1n1/p3

18. Liu, H., Jin, I. H., Zhang, Z., & Yuan, Y. (2021). Social network mediation analysis: A latent space Approach. Psychometrika . 86, 272–298 https://doi.org/10.1007/s11336-020-09736-z

17. Liu, R., & Liu, H. (2020) Nested diagnostic classification models for multiple-choice items. British Journal of Mathematical and Statistical Psychology, 74(2), 257-285, https://doi/abs/10.1111/bmsp.12214

16. Qu, W., Liu, H., & Zhang, Z. (2020). A Method of generating multivariate non-normal random numbers with desired multivariate skewness and kurtosis. Behavior Research Method, 52, 939-946

15. Liu, H., Jin, I. H., & Zhang, Z. (2018). Structural equation modeling of social networks: Specification, estimation, and application. Multivariate Behavioral Research, 53(5), 714-730. doi: 10.1080/00273171.2018.1479629.

*The recipient of the 2019 Tanaka Award for Best Article in Multivariate Behavioral Research.*

14. Zhang, Z., Jiang, K., Liu, H., & In-Sue Oh. (2018). Bayesian meta-analysis of correlation coefficients through power prior. Communications in Statistics - Theory and Methods. doi: 10.1080/03610926.2017.1288251

13. Liu, H., & Zhang, Z. (2017). Logistic regression with misclassification in binary outcome variables: a method and software. Behaviormetrika, 44(2), 447-476. doi: 10.1007/s41237-017-0031-y

12. Merluzzi, T. V., Philip, E. J., Heitzmann, C. A., Liu, H., Yang, M.,& Conley, C. (2018). Self-efficacy for coping with cancer: Revision of the Cancer Behavior Inventory (Version 3.0). Psychological Assessment. doi: 10.1037/pas0000483

11. Cheng, Y., & Liu. H. (2016). A short note on the maximal point-biserial correlation under non-normality. British Journal of Mathematical and Statistical Psychology, 69(3), 344-351. doi: 10.1111/bmsp.12075

10. Liu, H., Zhang, Z, & Grimm, K. J. (2016). Comparison of Inverse Wishart and separation-strategy priors for Bayesian estimation of covariance parameter matrix in growth curve analysis. Structural Equation Modeling: A Multidisciplinary Journal, 23(3), 354-367. doi: 10.1080/10705511.2015.1057285

9. Fey-den Boer, A., & Liu, H. (2011). Limiting shapes for a non-abelian sandpile growth model and related cellular automata. Journal of Cellular Automata, 6, 353-383.

8. Kager, W., A., Liu, H., & Meester, R. (2010). Existence and uniqueness of the stationary measure in the continuous Abelian sandpile. Markov Processes and Related Fields, 16 (1), 185-204.

7. Fey-den Boer, A., Liu, H., & Meester, R. (2009). Uniqueness of the stationary distribution and stabilizability in Zhangs sandpile model. Electronic Journal of Probability,14 (32), 895-911.

6. Liu, H. (2015). Review of The BUGS Book: A Practical Introduction to Bayesian Analysis, by David Lunn, Christopher Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter. Structural Equation Modeling: A Multidisciplinary Journal, 22 (2), 323-325. doi: 10.1080/10705511.2014.958046

Book Chapters and Encyclopedia

5. Qu, W., Liu, H., & Zhang, Z. (2020). Permutation Test of Regression Coefficients in Social Network Data Analysis. Quantitative Psychology, 377-387

4. Zhang, Z., & Liu, H. (2019). Sample Size and Measurement Occasion Planning for Latent Change Score Models through Monte Carlo Simulation. In E. Ferrer, S. M. Boker, & K. J. Grimm (Eds.), Advances in Longitudinal Models for Multivariate Psychology: A Festschrift for Jack McArdle.

3. Liu, H., & Zhang, Z. (2018). Probit Transformation. In B. Frey (Eds.). The Sage Encyclopedia of Educational Research, Measurement, and Evaluation. 1300. Sage.

2. Liu, H. (2017). Statistical Power Analysis for Logistic Regression. In Z. Zhang, & K.-H. Yuan (Eds.), Practical Statistical Power Analysis Using Webpower and R (pp. 149-158). Granger, IN: ISDSA Press.

Liu, H. (2017). Statistical Power Analysis for Poisson Regression. In Z. Zhang, & K.-H. Yuan (Eds.), Practical Statistical Power Analysis Using Webpower and R (pp. 159-169). Granger, IN: ISDSA Press.