Jialiang Li

E-mail: jialiang at nus.edu.sg
Phone: (65)6516-8932
Office: S16-07-111

Biostatistics; Change point; Diagnostic medicine; Instrumental variable; Network; Personalized medicine; Statistical learning.

Jiang, B; Lv, J; Li, J; Cheng, MY. (2024). Robust model averaging prediction of longitudinal response with ultrahigh-dimensional covariates. Journal of the Royal Statistical Society Series B. Accepted.
Liu, P [PhD student], Li, Y, Li, J. (2025). Change surface regression for nonlinear subgroup identification with application to warfarin pharmacogenomics data. Biometrics, Accepted.
Ding, J; Li, J; Xie, P; Wang, X (2024). Efficient risk assessment of time-to-event targets with adaptive information transfer. Statistics in Medicine. Accepted.
Zhao, D [PhD student], Xia, X, Li, J. (2025). A Varying-coefficient Additive Hazard Model for Recurrent Events Data. Statistics in Medicine. Accepted.
Liu, Y, Luo, S, Li, J. (2024). Hypothesis tests in ordinal predictive models with optimal accuracy. Biometrics. Accepted.
Yang, J, Kuan, P.F., Li, X., Li, J., Zhou, X. H. (2024). Transformed ROC Curve for Biomarker Evaluation. Statistics in Medicine. Accepted.
Ding, J., Li, J., Wang, X. (2024). Efficient auxiliary information synthesis for cure rate model. Journal of the Royal Statistical Society: Series C. 73(2):497-521.
Ding, J., Li, J., Wang, X. (2024). Renewable risk assessment of heterogeneous streaming time-to-event cohorts. Statistics in Medicine. 43(20):3761-3777.

Li, J. and Ma, S. (2013). Survival Analysis in Medicine and Genetics. Chapman & Hall/CRC Press.

Complete list of publications: cv

Associate Editor for Annals of Applied Statistics.
Associate Editor for Biometrics (2010-2018).
Associate Editor for Statistical Methods in Medical Research.
Editorial Committee for Annual Review of Statistics and Its Application.
Associate Editor for Lifetime Data Analysis.
Statistics Editor for BiOMARKERS.
Statistical Advisor for The British Journal of Psychiatry (BJPsych Open).
International Biometric Society (IBS) Budget and Finance Committee: 2016-2023.
International Chinese Statistical Association (ICSA), Board of Director, 2024-2026.

R code to evaluate HUM for three and four unordered categories, following Li, Fine and Pencina (2018) Statistical Theory and Related Fields. These files are now incorporated in an R package mcca available on CRAN and GitHub. May evaluate HUM for combined markers based on all sorts of learning methods. The package from GitHub allows Deep Learning.
R package HUM is now available on CRAN. May evaluate HUM for markers to differentiate large number (M>3) of categories.
R code to evaluate multi-category NRI and IDI, following Li, Jiang and Fine (2013) Biostatistics. Also incorporated in an R package mcca available on CRAN and GitHub.
R code to evaluate Polytomous Discrimination Index (PDI) for three and four classes, following Li, Feng, Fine, Pencina and Van Calster (2018) SMMR. Also incorporated in an R package mcca available on CRAN and GitHub.
R code for improvement screening, based on Yue and Li (2018) International Journal of Biostatistics.
R code to compute bootstrap confidence intervals and p-values for NRI and IDI. See Shao et al. (2015) Biomarkers.
R code for two stage multiple Change Point detection (TSMCP): example and scad penalty function following Li and Jin (2018) AOS.
ROC Matlab code: nonparametric and semiparametric ROC surface estimation. See Li and Zhou (2009) JSPI.