Chen Zehua

Professor of Statistics
Department of Statistics and Applied Probability
National University of Singapore
3 Science Drive 2, Singapore 117543
Republic of Singapore

stachenz@nus.edu.sg

(65) 6516-6307 (office)
(65) 6569-5659 (home)
(65) 6872-3919 (fax)

Education

  • B.S., Wuhan Univ. (1981)
  • M.S., Univ. of Iowa (1985)
  • Ph.D., Univ. of Wisconsin-Madison (1989)

Current interests

  • Model selection criteria.
  • Feature selection with high dimensional space.
  • Statistical genetics.

 

Science Lunchtime Talk (August 27, 2009):  An Adaptive Screen-selection Procedure for Feature selection in Small-n-large-p Problems

 

Publications

         Publication List  

Recent Preprints

    • A feature selection approach to case-control genome-wide association studies. (Full text)
    • Extended BIC for small-$n$-large-$P$ sparse GLM. (Full text)

 

Monograph

Ranked Set Sampling: Theory and Applications

Z. Chen,   Z. D. Bai and B. K. Sinha

Springer ©2004

                        Preface (PDF file)

                  Table of contents (PDF file)

 

Software

The package migtlm:   Multiple interval genetic trait loci mapping

       Source code: migtlm.R

       Instruction:    How to use?

       Reference:    Mixture Generalized Linear Models for Multiple Interval Mapping of Quantitative Trait Loci in Experimental Crosses

 

Teaching Corner

ST4241: Design and Analysis of Clinical Trials (2009/2010 Semester I)

                           Course Information

                      Statistical Tables for Tukey's and Dunnett's multiple comparison criteria

                            Lecture Notes 1: An overview of clinical trials

                            Lecture Notes 2: Parallel groups design

                                                       Tutorial 1  (R Code) (Solution)

                            Lecture Notes 3:  Special cases of parallel groups study

                                                       Tutorial 2 (R Code) (Solution)

                                                       Tutorial 3 (R Code) (Solution)

                            Lecture Notes 4:  Blocking to control prognostic variables (R Code)

                                                       Tutorial 4 (R Code) (Solution)

                                                       Tutorial 5 (R Code) (Solution)

                                                       Midterm Exam Paper

                            Lecture Notes 5:  Stratification to control prognostic variables (R Code)

                                                       Tutorial 6 (R Code) (Solution)

                            Lecture Notes 6:  Regression control for prognostic variables

                                                       Tutorial 7 (R Code) (Solution)

                            Lecture Notes for E-learning week:  Repeated Measurements Studies (R Code)

                                                       Tutorial 8 (R Code) (Solution)

                            Lecture Notes 7:  Latin and Greco-Latin squares design for particular prognostic variable control (R Code)

                                                       Tutorial 9  (Second assignment) (Solution)

                            Lecture Notes 8:   Crossover study to control subject unit effects

                                                       Tutorial 10 (Solution)

                            Lecture Notes 9:   Balanced incomplete block design

                                                       Tutorial 11 (Solution)

                            Lecture Notes 10:   Issues on the determination of trial size

 

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Chen Zehua <stachenz@nus.edu.sg>