Methodological Publications

Submitted/Under Revision

Liu, Y., & Pek, J. Summed versus estimated factor scores: Considering uncertainties when using observed scores.

Liu, Y., & Wang, W. What can we learn from a semiparametric factor analysis of item responses and response time? An illustration with the PISA 2015 data.

Liu, Y., Hannig, J., & Murph, A. C. A Geometric Perspective on Bayesian and Generalized Fiducial Inference.

Morell, M., Liu, Y., & Yang, J. A regression discontinuity model with latent variables.

In Press

Liu, Y., & Sweet T. M. Statistical inference: Bayesian approaches. In Tierney, R., Rizvi, F., and Ercikan, K. (Eds.), International Encyclopedia of Education, 4th Edition. Oxford: Elsevier Ltd.


Magnus, B. E., & Liu, Y. (2022). Symptom presence and symptom severity as unique indicators of psychopathology: An application of multidimensional zero-inflated and hurdle graded response models. Educational and Psychological Measurement, 82(5), 938-966.

Wang, W., Liu, Y., & Liu, H. (2022). Testing differential item functioning without predefined anchor items using robust regression. Journal of Educational and Behavioral Statistics, 47(6), 666-692.

Xu, S., & Liu, Y. (2022). Characterizing sampling variability for projected IRT scores in a fixed-item-parameter linking design. Applied Psychological Measurement, 46(6), 509-528.

Liu, Y., & Wang, W. (2022). Semiparametric factor analysis for item-level response time data. Psychometrika, 87(2), 666-692.


Liu, Y. (2021). Riemannian Newton and trust-region algorithms for analytic rotation in exploratory factor analysis. British Journal of Mathematical and Statistical Psychology, 74(1), 139-163.

Tian, C., & Liu, Y. (2021). A rotation criterion that encourages a hierarchical factor structure. In Wiberg, M., Molenaar, D., González, J., Böckenholt, U., and Kim, J.-S. (Eds.), Proceedings of the 85th Annual (Virtual) Meeting of the Psychometric Society. New York, NY: Springer.


Liu, Y. (2020). A Riemannian optimization algorithm for joint maximum likelihood estimation of high-dimensional exploratory item factor analysis. Psychometrika, 85(2), 439-468.

Wang, X., & Liu, Y. (2020). Detecting compromised items using information from secure items. Journal of Educational and Behavioral Statistics, 45(6), 667-689.

Zhang, S., Chen, Y., & Liu, Y. (2020). An improved stochastic EM algorithm for large-scale full-information item factor analysis. British Journal of Mathematical and Statistical Psychology, 73(1), 44–71.

Man, K., Harring, J. R., & Liu, Y. (2020). Abstract: Methods of integrating multi-modal data for assessing aberrant test-taking behaviors. Multivariate Behavioral Research, 55(1), 155–156.

Morell, M., Yang, J. S., & Liu, Y. (2020). Abstract: Latent variable regression discontinuity design with cluster level treatment assignment. Multivariate Behavioral Research, 55(1), 146.


Haberman, S., Liu, Y., & Lee, Y.-H. (2019). Distractor analysis for multiple-choice tests: An empirical study with international language assessment data. ETS Research Report Series, 19(39), 1-16.

Liu, Y., Hannig, J., & Pal Majumder, A. (2019). Second-order probability matching priors for the person parameter in unidimensional item response theory models. Psychometrika, 84(3), 529–553.

Wang, X., Liu, Y., Robin, F., & Guo, H. (2019). A comparison of methods for detecting examinee preknowledge of items. International Journal of Testing, 19(3), 207–226.

Liu, Y., Yang, J. S., & Maydeu-Olivares, A. (2019). Restricted recalibrations of item response theory models. Psychometrika, 84(2), 529–553.


Magnus, B., & Liu, Y. (2018). A zero-inflated Box-Cox normal unipolar item response model for measuring constructs of psychopathology. Applied Psychological Measurement, 42(7), 571–589.

Chen, Y., Liu, Y., & Xu, S. (2018). Mutual information reliability for latent class analysis. Applied Psychological Measurement, 42(6), 460–477.

Liu, Y. & Yang, J. S. (2018). Bootstrap-calibrated interval estimates for latent variable scores in item response theory. Psychometrika, 83(2), 333-354.

Liu, Y., & Yang, J. S. (2018). Interval estimation of scale scores in item response theory. Journal of Educational and Behavioral Statistics, 43(3), 259–285.

Liu, Y., Magnus, B., Quinn, H., & Thissen, D. (2018). Multidimensional item response theory. In Hughes, D., Irwing, P., and Booth, T. (Eds.), Handbook of Psychometric Testing (pp. 445–493). Chichester, West Sussex: Wiley-Blackwell.

Yang, J. S., Morell, M., & Liu, Y. (2018). Constructed-response items. In Frey, B., (Ed.), The SAGE Encyclopedia of Educational Research, Measurement, and Evaluation (pp. 381-383). Los Angeles, CA: SAGE Publications, Inc.

Depaoli, S., &, Liu, Y. (2018). Book Review: Bayesian Psychometric Modeling. Psychometrika, 83(2), 511–514.


Chalmers, R. P., Pek, J., & Liu, Y. (2017). Profile-likelihood confidence intervals in item response theory models. Multivariate Behavioral Research, 52(5), 533–550.

Wang, X., Liu, Y., & Hambleton, R. K. (2017). Detecting candidate preknowledge of items using a predictive checking method. Applied Psychological Measurement, 41(4), 243-263.

Liu, Y. & Hannig, J. (2017). Generalized fiducial inference for logistic graded response models. Psychometrika, 82(4), 1097–1125.


Liu, Y., & Hannig, J. (2016). Generalized fiducial inference for binary logistic item response models. Psychometrika, 81(2), 290–324.

Liu, Y., Magnus, B. E., & Thissen, D. (2016). Modeling and testing differential item functioning in unidimensional binary item response models with a single continuous covariate: A functional data analysis approach. Psychometrika, 81(2), 371–398.


Maydeu-Olivares, A., & Liu, Y. (2015). Item diagnostics in multivariate discrete data. Psychological Methods, 20(2), 276–292.

Before 2015

Liu, Y. & Thissen, D. (2014). Comparing score tests and other local dependence diagnostics for the graded response model. British Journal of Mathematical and Statistical Psychology, 67(3), 496–513.

Liu, Y., & Maydeu-Olivares, A. (2014). Identifying the source of misfit in item response theory models. Multivariate Behavioral Research, 49(4), 354–371.

Liu, Y., & Hannig, J. (2014). Abstract: Generalized fiducial inference for binary logistic item response models. Multivariate Behavioral Research, 49(3), 290.

Liu, Y. & Maydeu-Olivares, A. (2013). Local dependence diagnostics in IRT modeling of binary data. Educational and Psychological Measurement, 73(2), 254–274.

Liu, Y. & Thissen, D. (2012). Identifying local dependence with a score test statistic based on the bifactor logistic model. Applied Psychological Measurement, 36(8), 670–688.