Refereed Journal Articles (§) author was a student when the research was conducted; (*) equal contribution.
§Song, X., Zhang, Q., §Ye, K., & Linero, A. R. (submitted) Automatic Mediation Analysis Under Measurement Error Via Bayesian Machine Learning.
Zhang, Q., §Lei, H., §Swanson, P., Cao, H., & Slate, E. H. (submitted). Variable Selection for Explaining Inter-Individual Heterogeneity in Longitudinal Growth Trajectories.
Zhang, Q., Liu, X., & Ke, Z. (R&R). Best Practices in Multilevel Modeling for Within-Cluster Group Comparisons: An Evaluation of Coding Strategies Reflecting Group Composition and Heterogeneity. Psychological Methods.
Hughes, R., §Wang, Q., Dominguez, R., Lucas, K., Ndubuisi, S., Britsch, B., Levinsky-Raskin, S., Sullivan, A., & Zhang, Q. (R&R). The Bright Future of Online Programming for Girls' STEM Identity Development.
§Chen, S., Phillips, B.M. & Zhang, Q. (in press). Understanding Teacher-Child Relationship Dynamics in Head Start: The Roles of Children’s Gender, Undesired Behavior, and Teachers’ Job Stress. Early Childhood Education Journal. https://doi.org/10.1007/s10643-025-01945-4
§Ha, C., Zhang, Q., & Roehrig, A. D. (2025). Early adolescents’ motivational regulation and academic achievement: Using multi-level modeling analysis based on self-determination theory. Social Psychology of Education, 28(1), 10. http://doi.org/10.1007/s11218-024-10013-5
§Lu, Z., Ke, Z., Cheung, R. Y. M., & Zhang, Q. (2025). Synthesizing data from pretest-posttest-control-group designs in mediation meta-analysis. Behavior Research Methods, 57(5), 146. https://doi.org/10.3758/s13428-025-02661-y
Linero, A. R., & Zhang, Q. (2025). Mediation analysis using Bayesian tree ensembles. Psychological Methods, 30(1), 60–82. https://doi.org/10.1037/met0000504
§Liu, L., & Zhang, Q. (2025). Latent Interaction Modeling with Ordinal Items: Evaluating Alternative Analytic Methods and Parceling Strategies. Structural Equation Modeling: A Multidisciplinary Journal, 32(4), 657–677. https://doi.org/10.1080/10705511.2025.2487678
Zhang Q. (2024). Comparing methods for assessing a difference in correlations with dependent groups, measurement error, nonnormality, and incomplete data. Psychological Methods, 29(4), 767–788. https://doi.org/10.1037/met0000522
Becker, B. J., & Zhang, Q. (2024). Advances in meta-analysis: A unifying modelling framework with measurement error correction. British Journal of Mathematical and Statistical Psychology, 77, 395–428. https://doi.org/10.1111/bmsp.12345
§Wang, Q., *Hall, G. J., *Zhang, Q., & §Comella, S. (2024). Predicting Implementation of Response to Intervention (RTI) in Math Using Elastic Net Logistic Regression. Frontiers in Psychology: Quantitative Psychology and Measurement. https://doi.org/10.3389/fpsyg.2024.1410396
Zhang, Q., & §Wang, Q. (2024). Handling Measurement Error and Omitted Confounders Considering Informativeness of the Confounding Effect under Mediation Modeling. Structural Equation Modeling: A Multidisciplinary Journal, 31(6), 1083–1103. https://doi.org/10.1080/10705511.2023.2270167
Zhang, Q., & §Wang, Q. (2024). Correcting for measurement error under meta-analysis of z-transformed correlations. The British journal of mathematical and statistical psychology, 77(2), 261–288. https://doi.org/10.1111/bmsp.12328
Zhang, Q. (2024). Meta-analysis of correlation coefficients: A cautionary tale on treating measurement error. Psychological Methods, 29(2), 308–330. https://doi.org/10.1037/met0000498
§Lin, Q., Nuttall, A. K., Zhang, Q., & Frank, K. A. (2023). How do unobserved confounding mediators and measurement error impact estimated mediation effects and corresponding statistical inferences? Introducing the R package ConMed for sensitivity analysis. Psychological Methods, 28(2), 339–358. https://doi.org/10.1037/met0000567
§Ha, C., Roehrig, A. D., & Zhang, Q. (2023). Self-regulated learning strategies and academic achievement in South Korean 6th-graders: A two-level hierarchical linear modeling analysis. PLoS ONE, 18(4): e0284385. https://doi.org/10.1371/journal.pone.0284385
§Liu, L., & Zhang, Q. (2023). Parceling Ordinal Items in Latent Interaction Modeling. Multivariate Behavioral Research, 58(1), 143–144.
§Wang, Q., & Zhang, Q. (2023). Cross-Lagged Panel Analysis with Ordinal Items. Multivariate Behavioral Research, 58(1), 152–153.
Ho, S., Nickerson, J., & Zhang, Q. (2023). Hive Mind Online: Collective Sensing in Times of Disinformation. Journal of Digital Social Research, 4(4), 89-129. https://doi.org/10.33621/jdsr.v4i4.119
§Colgary, C., Swanbrow Becker, M., Zhang, Q., & §Konopa, J. (2022). An Examination of a Cognitive Dissonance Body Image and Health Intervention for the College Classroom. Journal of Prevention and Health Promotion, 3(4), 563–588. https://doi.org/10.1177/26320770221111759
Yang, Y., §Luo, Y., & Zhang, Q. (2021). A cautionary note on the identification and scaling issues in second-order latent growth models. Structural Equation Modeling: A Multidisciplinary Journal, 28, 302-313. Retrieved from 10.1080/10705511.2020.1747938
§Rahimi, S., Shute, V., & Zhang, Q. (2021). The effect of game difficulty and conceptual difficulty on student persistence in a learning game: A hierarchical linear modeling approach. International Journal of Technology in Education and Science, 5, 141-165. doi:https://doi.org/10.46328/ijtes.118
Zhang, Q., & Yang, Y. (2020). Autoregressive mediation models using composite scores and latent variables: Comparisons and recommendations. Psychological Methods, 25, 472-495. doi:https://doi.org/10.1037/met0000251 Click here for Mplus code.
§Xu, J., Zhang, Q., & Yang, Y. (2020). Impact of Violations of Measurement Invariance in Cross-lagged Panel Mediation Models. Behavior Research Methods, 52, 2623–2645. doi:https://doi.org/10.3758/s13428-020-01426-z
Wang, L., & Zhang, Q. (2020). Investigating the impact of time intervals and time lags on autoregressive mediation modeling: Some novel findings, implications, and recommendations. Psychological Methods, 25, 271-291. doi:https://doi.org/10.1037/met0000235
Zhang, Q., Yuan, K-H, & Wang, L. (2019). Asymptotic bias of normal-distribution-based maximum likelihood estimates of moderation effects with data missing at random. British Journal of Mathematical and Statistical Psychology, 72, 334-354. doi:https://doi.org/10.1111/bmsp.12151
*Ke, Z., *Zhang, Q., & Tong, X. (2019). Bayesian meta-analytic SEM: A one-stage approach to modeling between-study heterogeneity in structural parameters. Structural Equation Modeling: A Multidisciplinary Journal, 26, 348-370. doi:https://doi.org/10.1080/10705511.2018.1530059
§Velasquez, G., & Zhang, Q. (2019). Cross-lagged Panel Mediation Models with Latent Constructs: Specification and Estimation (abstract). Multivariate Behavioral Research, 55, 142-143. doi:https://doi.org/10.1080/00273171.2019.1695569
Nuttall, A. K., Zhang, Q., Valentino, K., & Borkowski, J. G. (2019). Intergenerational risk of parentification and infantilization to externalizing moderated by child temperament. Journal of Marriage and Family, 81, 648-661. doi:https://doi.org/10.1111/jomf.12562
Wang, L., Zhang, Q., Maxwell, S. M., & Bergeman, C. S. (2019). On estimating within-person relations: Standardized person-mean centering may not yield accurate estimates even when there are no trends. Multivariate Behavioral Research, 54, 382-403. doi:10.1080/00273171.2018.1532280
Englert, C., Havik, L., Zhang, Q., & Oudejans, R. R. D. (2018). Can you go the extra mile? The effect of ego depletion on endurance performance. International Journal of Sport Psychology, 49, 505–520. doi:https://doi.org/10.7352/IJSP.2018.49.505
Samuel, R., Englert, C., Zhang, Q., & Basevitch, I. (2018). Hi ref, are you in control? Self-control, ego-depletion, and performance in soccer referees. Psychology of Sport & Exercise, 38, 167-175. doi:https://doi.org/10.1016/j.psychsport.2018.06.009
Zhang, Q., Wang, L., & Bergeman, C. S. (2018). Multilevel autoregressive mediation models: Specification, estimation, and applications. Psychological Methods, 23, 278-297. doi:http://dx.doi.org/10.1037/met0000161 Click here to download R code for fitting MAMM in the empirical example.
Zhang, Q., & Phillips, B. M. (2018). Three-level longitudinal mediation with nested units: How does an upper-level predictor influence a lower-level outcome via an upper-level mediator over time? Multivariate Behavioral Research, 53, 655-675. doi:10.1080/00273171.2018.1471975
Zhang, Q., & Wang, L. (2017). Moderation analysis with missing data in the predictors. Psychological Methods, 22, 649-666. doi:http://dx.doi.org/10.1037/met0000104
Zhang, Q., & Wang, L. (2015). Evaluating methods for moderation analysis with missing data in the predictors (abstract). Multivariate Behavioral Research, 50(1), 144-145. doi:https://doi.org/10.1080/00273171.2014.989017
Zhang, Q., & Wang, L. (2014). Aggregating and testing intra-individual correlations: Methods and comparisons. Multivariate Behavioral Research, 49(2), 130-148. doi:https://doi.org/10.1080/00273171.2013.870877
Han, P., Lu, L., Zhang, Q., & Dong, Z. (2010). PID controller parameter estimation based on particle swarm optimization (PSO) guided by empirical formulas. Journal of North China Electric Power University:Natural Science Edition, 37, 73-77.
Han, P., Dong, Z., & Zhang, Q. (2008). Development of Automation Theory and Its Application in Power Plants. Journal of North China Electric Power University:Natural Science Edition, 6.
Refereed Proceedings
Zhang, Q., Dong, Z., Han, P., Wu, Z., & Gao, F. (2008). The optimization of controller parameters in thermal system using initial pheromone distribution in ant colony optimization. In IEEE International Conference on Information Reuse and Integration (pp. 22-27). Las Vegas, NV.
Wang, T., Zhou, L., Han, P., & Zhang, Q. (2007). Complete Compensation for Time Delay in Networked Control System Based on GPC and BP Neural Network. In IEEE International Conference on Machine Learning and Cybernetics. Hong Kong, China.