Book chapters

Computational Neuroscience and Cognitive Modelling (Anderson, 2014) (in Chinese)

Translated the part of Neural Networks (chapter 9-13).

Advanced Psychometric Measurement and Latent Variable Modeling (in Chinese)

Wrote the Bayesian Structural Equation Modeling chapter.


Journal articles

Note: * indicates correspondent author, Advances in Psychological Science was rated as one of the most influential Chinese journal, 2019.

Zhang, X.D., Zhang, L.J., Ding, Y.L., Qu, Z.* (accepted). Behavioral Oscillations in Attention. Advances in Psychological Science (in Chinese).

Feng, Q.Q., Song, Q.Y. (co-first author), Zhang, L.J. (co-first author), Zheng, S.F., Pan, J.H.* (accepted). Integration of Moderation and Mediation in a Latent Variable Framework: A Comparison of Estimation Approaches for the Second-stage Moderated Mediation Model. Frontiers in Psychology. [2019 IF: 2.067]

Zhang, L.J., Wei, X.Y., Lu, J.Q., Pan, J.H.* (2020). Lasso Regression: From Explanation to Prediction. Advances in Psychological Science (in Chinese), 28(10): 1777-1788.

Chen, J.S.*, Guo, Z.H., Zhang, L.J., Pan, J.H.* (2020). A Partially Confirmatory Approach to Scale Development with the Bayesian Lasso. Psychological Methods. Advance online publication. [2019 IF: 8.43] [My Participation]

Liu, S.J., Huang, Z.Z., Zhang, L.J., Pan, J.H., Lei, Q.F., Meng, Y.Y., Li, Z.* (2020). Plasma Neurofilament Light Chain may be a Biomarker for the Inverse Association between Cancers and Neurodegenerative Diseases. Frontiers in Aging Neuroscience, 12(10): 1-8. [2019 IF: 4.362]

Zhang, L.J., Lu, J.Q., Wei, X.Y., Pan, J.H.* (2019). Bayesian Structural Equation Modeling and its Current Research. Advances in Psychological Science (in Chinese), 27(11): 1812-1825.


Manuscripts under Review and in Preparation

Zhang, L.J., Pan, J.H.*, Dubé, L., Ip, E.H. (under review). BLCFA: An R Package for Bayesian Model Modification in Confirmatory Factor Analysis. Structural Equation Modeling: A Multidisciplinary Journal

Sun, R.Q., Zhang, L.J., Pan, J.H.* (manuscript drafted). Sample Size Determination Guidelines for Latent Mediation Model: A Monte Carlo Study.

Wei, X.Y., Huang, J.S. (co-first author), Zhang, L.J., Pan, J.H.* (manuscript drafted). Evaluation and Comparison among SEM, ESEM and BSEM in Estimating Structural Models with Potentially Unknown Cross-loadings.

Zhang, L.J., Ip, E.H., Pan, J.H.* (manuscript drafted). Comparison Between Effect Size, p-value, and Credible Interval in Variable Selection using the Bayesian Lasso Method


Talks

Zhang, L.J., Pan, J.H.*, Ip, E.H. (2020). BLCFA: An R package for Bayesian Model Modification in Confirmatory Factor Analysis. International Meeting of the Psychometric Society, 14-17 July, Online. [abstract]

Zhang, L.J., Wei, X.Y., Lu, J.Q., Pan, J.H.* (2019). Lasso Regression: From Explanation to Prediction. The 22nd Chinese Academic Conference of Psychology, 18-20 October, Hangzhou. [abstract] [slide]

Song, Q.Y., Pan, J.H., Zhang, L.J. (2019). Bayesian Multiple-group Analysis: Approximate Measurement Invariance. The 22nd Chinese Academic Conference of Psychology, 18-20 October, Hangzhou.

Zhang, L.J., Lu, J.Q., Wei, X.Y., Pan, J.H.* (2019). Bayesian Structural Equation Modeling and its Current Research. The 22nd Chinese Academic Conference of Psychology, 18-20 October, Hangzhou. [abstract] [slide]

Zhang, L.J., Pan, J.H.* (2019, Excellent Presenter). How to Select Prior Variance in Bayesian Approximate Measurement Invariance ? The 22nd Chinese Academic Conference of Psychology, 18-20 October, Hangzhou.[slide]

Zhang, L.J., Pan, J.H.* (2019). How to Select Prior Variance in Bayesian Approximate Measurement Invariance ? The International Meeting of the Psychometric Society, 15-19 June, Santiago. [abstract] (accepted but wasn’t able to attend)

Zhang, L.J., Lu, J.Q., Wei, X.Y., Pan, J.H.* (2019, Invited). Bayesian Structural Equation Modeling and its Current Research. The 12th China-R Conference, 24-26 May, Beijing. [slide]

Zhang, L.J., Lu, J.Q., Wei, X.Y., Pan, J.H.* (2019). Bayesian Structural Equation Modeling and its Current Research. Weekly Forum of Psychology in Sun Yat-sen University, 20 November, Guangzhou.

Pan, J.H., Zhang, L.J., Ip, E.H.* (2018). Bayesian Lasso Factor Analysis Models with Ordered Categorical Data. The 13th Cross-Straits Conference on Educational and Psychological Testing, 22-25 October, Taiwan. [slide]

Pan, J.H., Zhang, L.J., Ip, E.H.* (2017). Bayesian Lasso Factor Analysis Models with Ordered Categorical Data. The 20th Chinese Academic Conference of Psychology, 3-5 November, Chongqing. [abstract]


Posters

Zhang, L.J., Lu, J.Q., Zhang, Y.N., Pan, J.H.* (2019). The Influence of Social Support on Career Decision-Making Difficulty: Bayesian Modeling Based on Longitudinal Data. The 22nd Chinese Academic Conference of Psychology, 18-20 October, Hangzhou. [abstract][poster]

Zhang, L.J., Lu, J.Q., Zhang, Y.N., Pan, J.H.* (2018, Excellent Presenter). The Influence of Social Support on Career Decision-Making Difficulty: A Moderated Mediation Model. Psychology Academic Forum for the 21st Century, 24-26 March, Beijing.


Software Development

Zhang, L.J., Pan, J.H., Ip, E.H. (2020). BLCFA: An R Package for Bayesian Model Modification in Confirmatory Factor Analysis. Retrievable from https://github.com/zhanglj37/blcfa.

Zhang, L.J., Sun, R,Q., Pan, J.H. (2020). sampleMplus: An R Package for Sample Size Determination in Structural Equation Modeling. Retrievable from https://github.com/zhanglj37/sampleMplus.



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