Jialiang Li

Associate Professor
Department of Statistics & Applied Probability
National University of Singapore

             Phone: (65)6516-8932
                                                            stalj@nus.edu.sg

 

Adjunct Appointment

Duke-NUS Graduate Medical School
Singapore Eye Research Institute

Education

  • PhD in Statistics 2006
    University of Wisconsin, Madison
  • BS in Statistics 2001
    University of Science and Technology of China

 

Current Interests

High dimensional data; Diagnostic medicine; Survival analysis.

Recent Works

  • Li, J., Huang, C., Zhu, H. (2017). A Functional Varying-Coefficient Single Index Model for Functional Response Data. Journal of the American Statistical Association (T&M). Accepted.
  • Li, J., Feng, Q., Fine, J.P., Pencina, M.J., Van Calster, B. (2017). Nonparametric estimation and inference for polytomous discrimination index. Statistical Methods in Medical Research. Accepted.
  • Li, J., Jin, B. (2017). Multi-threshold Accelerated Failure Time Model. Annals of Statistics. Accepted.
  • Fang, X. [PhD student], Li, J., Wong, W. K., and Fu, B. (2016). Detecting the Violation of Variance Homogeneity in Mixed Models: a Case Study. Statistical Methods in Medical Research. 25(6): 2506-2520.
  • Cheng, M., Honda, T., Li, J. (2016). Efficient estimation in semivarying coefficient models for longitudinal/clustered data. The Annals of Statistics. 44(5): 1988-2017.
  • Ke, Y., Li, J., Zhang, W. (2016). Structure Identification in Panel Data Analysis. The Annals of Statistics. 44(3): 1193-1233.
  • Huang, Z. [PhD student], Li, J., Cheng, C.Y., Cheung, C., Wong, T.Y. (2016). Bayesian reclassification statistics for assessing improvements in diagnostic accuracy. Statistics in Medicine. 35(15): 2574-2592.
  • Li, J., Zheng, Q., Peng, L., Huang, Z. (2016). Survival impact index and ultrahigh-dimensional model-free screening with survival outcomes. Biometrics. 72(4): 1145-1154.
  • Li, J., Fine, J. and Brookhart, A. (2015). Instrumental variable additive hazards models. Biometrics. 71: 122-130.
  • Shao, F. [PhD student], Li, J., Ma, S. and Lee, M.-L.T. (2014). Semiparametric Varying-coefficient Model for Interval Censored Data with a Cured proportion. Statistics in Medicine. 33(10): 1700—1712.
  • Natalia Novoselova, Cristina Della Beffa, Junxi Wang , Jialiang Li, Frank Pessler, Frank Klawonn (2014). HUM Calculator and HUM package for R: easy-to-use software tools for multicategory receiver operating characteristic analysis. Bioinformatics. 30(11):1635-6.
  • Salim, A., Ma, X., Li, J., Reilly, M. (2014). A maximum likelihood method for secondary analysis of nested case-control data. Statistics in Medicine. 33(11):1842-52.
  • Kuk, A. Y. C., Li, J. and Rush, J. A. (2014). Variable and threshold selection to control predictive accuracy in logistic regression. Applied Statistics. 63:657-672.
  • Cheng, M.Y., Honda, T., Li, J., Peng, H. (2014). Nonparametric independence screening and structural identification for ultra-high dimensional longitudinal data. The Annals of Statistics. 42(5): 1819-1849.
  • Li, J., Jiang, B. and Fine, J. P. (2013). Multicategory reclassification statistics for assessing Improvements in diagnostic accuracy. Biostatistics. 14(2): 382-394.
  • Li, J., Jiang, B. and Fine, J. P. (2013). Letter to Editor: Response. Biostatistics. 14(4): 809-810.

Monograph

Complete list of publications: cv

Professional Services

  • Associate Editor for Biometrics (since 2010).
  • Associate Editor for Lifetime Data Analysis (since 2014).
  • Associate Editor for Biostatistics & Epidemiology (since 2016).
  • Associate Editor for Communications for Statistical Applications and Methods (since 2017).
  • Statistics Editor for BiOMARKERS (since 2010).

Open Source

  • R code to evaluate HUM for three and four unordered categories, following Li and Fine (2008). Related files: Program and Examples
  • R package HUM is now available on CRAN.
  • R code to evaluate NRI and IDI, following Li, Jiang and Fine (2013). Alternative calculation using SVM.
  • R code to evaluate Polytomous Discrimination Index (PDI) for three and four classes, following Li, Feng, Fine, Pencina and Van Calster (2017).
  • R code for improvement screening .
  • R code to compute bootstrap confidence intervals and p-values for NRI and IDI.
  • R code for two stage multiple Change Point detection (TSMCP): example and scad penalty function following Li and Jin (2017).
  • R code to evaluate model-based and empirical outlier tests in mixed models for normal and Poisson responses.
  • CV Matlab code: fast evaluation of cross validation in semiparametric model.
  • MD-ED100p R code: estimation and confidence regions of Multi-Dimensional Effective Dose.
  • ROC Matlab code: nonparametric and semiparametric ROC surface estimation.
  • HDSD SAS code: analysis of NASA HDSD data — random effects model.
  • TD Matlab code: estimation of two-dimensional toxic dose based on multivariate logistic model.
  • Two data sets for paper by Zhang and Li (2011): Example 1, Example 2

Lectures

  • ST1131: INTRODUCTION TO STATISTICS (Spring 2012)
  • ST3131: REGRESSION ANALYSIS (Spring 2011)
  • ST4241: DESIGN AND ANALYSIS OF CLINICAL TRIALS (Fall 2011, 2013, 2014)
  • ST4242: ANALYSIS OF LONGITUDINAL DATA (Spring 2007, 2008, 2009 & 2010)
  • ST5203: EXPERIMENTAL DESIGN (Fall 2009)
  • ST5206: GENERALIZED LINEAR MODEL (Fall 2010)
  • ST5212: SURVIVAL ANALYSIS (Fall 2007)
  • ST5217: Statistical Methods for Genetic Analysis (Spring 2014)
  • ST5318: STATISTICAL METHODS FOR HEALTH SCIENCES (Fall 2006)