Contact Information
Research Areas
Research Interests
Personnel selection (e.g., applicant faking, forced-choice measurement)
Personality (e.g., personality assessment, relationships of Big 5 with stress, health, and workplace outcomes)
Research methods (e.g., IRT, SEM, bifactor models, longitudinal analysis)
Education
PhD, Industrial and Organizational Psychology, University of Illinois Urbana-Champaign, 2020
MS, Applied Statistics, University of Illinois Urbana-Champaign, 2020
MS, Psychological Measurement, Beijing Normal University, 2015
BS, Psychology, Beijing Normal University, 2012
Additional Campus Affiliations
Assistant Professor, School of Labor and Employment Relations
External Links
Highlighted Publications
Forced-choice measurement
Zhang, B., Tu, N., Angrave, L.C., Zhang, S., Sun, T., Tay, L. & Li, J. (In press). The Generalized Thurstonian Unfolding Model (GTUM): Advancing the modeling of forced-choice data. Organizational Research Methods.
Zhang, B., Luo, J., & Li, J. (2023). Moving beyond Likert and traditional forced-choice scales: A comprehensive investigation of the graded forced-choice format. Multivariate Behavioral Research.
Zhang, B., Sun, T., Drasgow, F., Chernyshenko, O.S., Nye, C., Stark, S., & White, L.A (2020). Though forced, still valid: Psychometric equivalence of forced choice and single statement measures. Organizational Research Methods, 22(3), 569-590.
Bifactor modeling
Zhang, B., Luo, J., Zhang, S., Sun, T., & Zhang, D.C. (In press). Improving the statistical performance of oblique bifactor measurement and predictive models: An augmentation approach. Structural Equation Modeling: A Multidisciplinary Journal.
Zhang, B., Luo, J., Sun, T., Cao, M., & Drasgow, F. (2023). Small but Nontrivial: A Comparison of Six Strategies to Handle Cross-Loadings in Bifactor Predictive Models. Multivariate Behavioral Research, 58(1), 115-132.
Zhang, B., Sun, T., Cao, M., & Drasgow, F. (2021). Using bifactor models to examine the predictive validity of hierarchical constructs: Pros, cons, and solutions. Organizational Research Methods, 24(3), 530-571.
Personality & Outcomes
Luo, J., Zhang, B., Graham, E.K., & Mroczek, D.K. (In press). Does personality always matter for health? Examining the moderating effect of age on the personality-health link from life-span developmental and aging perspectives. Journal of Personality and Social Psychology.
Luo, J., Zhang, B., Cao, M., & Roberts, B. W. (2023). The Stressful Personality: A meta-analytical review of the relation between personality and stress. Personality and Social Psychology Review, 27(2), 128–194.
Luo, J., Zhang, B., Estabrook, R., Schalet, B.D., Graham, E.K., Driver, C.C., Turiano, N.A., Spirio III, A., & Mroczek, D.K. (2022). Personality and health: Disentangling their between-person and within-person relationship in three longitudinal studies. Journal of Personality and Social Psychology, 122(3),493-522.
Recent Publications
Luo, J., Zhang, B., Antonoplis, S., & Mroczek, D. K. (2024). The effects of socioeconomic status on personality development in adulthood and aging. Journal of Personality, 92(1), 243-260. https://doi.org/10.1111/jopy.12801
Shi, D., Zhang, B., Liu, R., & Jiang, Z. (2024). Evaluating Close Fit in Ordinal Factor Analysis Models With Multiply Imputed Data. Educational and Psychological Measurement, 84(1), 171-189. https://doi.org/10.1177/00131644231158854
Zhang, B., Luo, J., Zhang, S., Sun, T., & Zhang, D. C. (2024). Improving the Statistical Performance of Oblique Bifactor Measurement and Predictive Models: An Augmentation Approach. Structural Equation Modeling, 31(2), 233-252. https://doi.org/10.1080/10705511.2023.2222229
Fan, J., Sun, T., Liu, J., Zhao, T., Zhang, B., Chen, Z., Glorioso, M., & Hack, E. (2023). How Well Can an AI Chatbot Infer Personality? Examining Psychometric Properties of Machine-Inferred Personality Scores. Journal of Applied Psychology, 108(8), 1277-1299. https://doi.org/10.1037/apl0001082
Koenig, N., Tonidandel, S., Thompson, I., Albritton, B., Koohifar, F., Yankov, G., Speer, A., Hardy, J. H., Gibson, C., Frost, C., Liu, M., McNeney, D., Capman, J., Lowery, S., Kitching, M., Nimbkar, A., Boyce, A., Sun, T., Guo, F., ... Newton, C. (2023). Improving measurement and prediction in personnel selection through the application of machine learning. Personnel Psychology, 76(4), 1061-1123. https://doi.org/10.1111/peps.12608