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田国梁

教授  

0755-88018757

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个人简介

田国梁,南方科技大学数学系统计学教授、博士生导师。1988年获得武汉大学统计学硕士学位、1998年获得中国科学院应用数学研究所的统计学博士学位。从1998至2002年, 他分别在北京大学概率统计系和美国田纳西州孟斐斯市的 St. Jude 儿童研究医院生物统计系从事博士后研究, 2002年至2008年他在美国马里兰大学 Marlene and Stewart Greenbaum Comprehensive 癌症中心 Senior  Biostatistician。2008年至2016年他在香港大学统计及精算学系任副教授、博士生导师。田教授是国际统计学会 (ISI) 当选会员, 他担任 Computational Statistics & Data Analysis, Statistics and Its Interface 等四个国际统计学杂志的副主编。他主要的研究领域是生物统计, 计算统计和社会统计。目前的研究方向包括多元零膨胀计数数据分析、斜与非对称连续数据分析,  (0, 1) 区间上连续比率数据(以及其推广, 即成份数据)的统计分析, 不完全分类数据分析, 和大维随机矩阵的理论方法及应用。他首次提出的分组 Dirichlet 分布、套Dirichlet 分布和G分布在统计分布领域属于创造性的工作, 在生物统计中具有广泛而重要的应用; 他将非随机化的概念引入到敏感性问题的随机化应答技术中, 发展了一个称之为非随机化应答技术的新研究方向。他首次提出了一个新的组装分解 (assembly-decomposition) 方法用以构造MM算法中的替代函数, 为MM算法在统计学中的广泛应用开辟了新的通道. 2017年他的研究课题<<MM算法中的几类问题之研究及其应用>>获得国家自然科学基金面上项目的资助。2018年他(排名第二)与南方科技大学环境科学与工程学院郑焰讲席教授的联合研究课题<<中国北方地下水砷不同尺度空间非均质性驱动机制>> 获得国家自然科学基金重点项目的资助。


教育背景

1995.9 – 1998.7       中国科学院应用数学研究所 (其中有一年在香港浸会大学数学系),  北京,  统计学专业,  统计学博士

1985.9 – 1988.7       武汉大学,  武汉,  统计学系,  统计学硕士

1981.9 1985.7       湖南师范大学,  长沙,  数学系,  理学学士


工作经历

2016.8.1 – 至今              南方科技大学,  数学系,  统计学教授

2008.9.1 – 2016.7.31     香港大学,  统计与精算学系,  统计学副教授

2002.7.1 – 2008.8.31     马里兰大学(巴尔的摩市, 马里兰州, 美国) 医学院

                                      Marlene and Stewart Greenebaum Comprehensive Cancer Center, 

                                      生物统计学部,Senior Biostatistician

2002.7.1 – 2008.8.31     马里兰大学医学院,  流行病学和预防医学系,  Instructor

2000.5.1 – 2002.6.30     St. Jude 儿童研究医院 (孟菲斯市, 田纳西州, 美国), 生物统计系,博士后

1998.9.1 – 2000.4.30     北京大学, 概率统计系, 博士后

1988.8.1 – 1995.8.31     航空航天工业部, 中国运载火箭研究院, 702研究所, 助理工程师, 工程师, 高級工程师


专业学会资格

2000.5 – 至今 Member, American Statistical Association

2000.5 – 至今 Permanent Member,  International Chinese Statistical Association

2014.6 – 至今 Elected member,  International Statistical Institute (ISI)


学会与学术服务

2016.11 – 2020.11  中国现场统计研究会试验设计分会第10届理事会常务理事

2016.11 2020.11  中国数学会均匀设计分会第6届理事会常务理事

2018.11 2022.11  中国数学会概率统计分会第11届理事会常务理事

2018.11 2022.11  全国工业统计学教学研究会常务理事

2018.11 2023.11  高等教育出版社 "现代统计学系列丛书" 第2届编委会委员


荣誉

2017  入选深圳市海外高层次人才 "孔雀计划" (B类)


研究方向

生物统计:多元零膨胀计次数据分析,  不完全分类数据与缺失数据分析,  斜与非对称连续数据分析,

                 (0, 1) 区间上连续比率数据与成分数据分析,  约束参数模型与变量选择,  

                 药物组合研究的实验设计,  癌症临床试验与设计

计算统计:EM算法,  MM算法

社会统计:敏感性问题的抽样调查


国际统计杂志副主编

Statistics and Its Interface, 2013 --

Communications in Statistics - Theory and Methods, 2013 --
Communications in Statistics - Simulation and Computation, 2013 --

Computational Statistics and Data Analysis, 2014 --


Top生物统计杂志文章 (14 papers)

Biostatistics Journal 1: Statistical Methods in Medical Research [Impact Factor=4.472; Ranking No. 1 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (6 papers)


[1] Shen X, Ma CX, Yuen KC and Tian GL* (2019). Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data, in press.


[2] Tian GL, JU D,Yuen KC and Zhang C* (2018). New expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine, 27(8), 2459-2477.


[3] Tian GL, Zhang C* and Jiang XJ (2018). Valid statistical inference methods for a case-control study with missing data, 27(4), 1001–1023.


[4] Tian GL and Li HQ (2017). A new framework of statistical inferences based on the valid joint sampling distribution of observed counts in an incomplete contingency table, 26(4) 1712–1736.


[5] Tian GL, Tang ML, Wu Q and Liu Y (2017). Poisson and negative binomial item count techniques for surveys with sensitive question, 26(2), 931–947.


[6] Tian GL, Tang ML, Liu ZQ, Tan M and Tang NS (2011). Sample size determination for the non-randomized triangular model for sensitive questions in a survey, 20(3), 159-173.


Biostatistics Journal 2: Statistics in Medicine [Impact Factor=1.825; Ranking No. 3 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (7 papers)


[7] Pei YB, Tian GL and Tang ML (2014). Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomize clinical trials, 33(25), 4370-4386.


[8] Tang ML, Ling MH, Ling L and Tian GL (2010). Confidence intervals for a difference between proportions based on paired data, 29(1), 86-96.


[9] Tang ML, Ling MH and Tian GL (2009). Exact and approximate unconditional confidence intervals for proportion difference in the presence of incomplete data, 28, 625-641.


[10] Tian GL, Yu JW, Tang ML and Geng Z (2007). A new non-randomized model for analyzing sensitive questions with binary outcomes, 26(23), 4238-4252.


[11] Fang HB, Tian GL, Xiong XP and Tan M (2006). A multivariate random-effects model with restricted parameters: Application to assessing radiation therapy for brain tumors, 25(11), 1948-1959.


[12] Tan M, Fang HB, Tian GL and Houghton PJ (2005). Repeated-measures models with constrained parameters for incomplete data in tumor xenograft experiments, 24(1), 109-119.


[13] Tan M, Fang HB, Tian GL and Houghton PJ (2003). Experimental design and sample size determination for testing synergism in drug combination studies based on uniform measures, 22(13), 2091-2100.


Biostatistics Journal 3: Biometrics [Impact Factor=1.568; Ranking No. 4 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (1 paper)


[14] Tan M, Fang HB, Tian GL and Houghton PJ (2002). Small-sample inference for incomplete longitudinal data with truncation and censoring in tumor xenograft models, 58(3), 612-620.


招聘信息

南方科技大学数学系田国梁课题组招聘统计学博士后12名,  每年招聘统计学博士生1名, 硕士生1–3名, 有意者请联系: tiangl@sustech.edu.cn


一. 得奖 (Awards)


2011  2012 Research Output Prize, Faculty of Science of the University of Hong Kong

                     (A monetary award of HK$120,000 for research purposes)




二. 基金 (Grants)


1. Completed in China, USA and HKU


1.1  09/1/1998-08/31/2001, AD19820224, Natural Science Foundation of China.

       Co-Investigator (30% contribution).

1.2   01/1/1999-12/31/2000, China Postdoctoral Science Foundation.

       The second class. Principal-Investigator.

1.3   04/1/2004-3/31/2008,   R01 CA106767 (PI: Prof Ming TAN),  US$890,000 

      Division of Biostatistics, University of Maryland Greenebaum Cancer Center,

      Baltimore, Maryland, USA

Title: Design and Analysis of Pre-clinical Combination Studies.

      This grant is to develop innovative methods to optimally design and

      efficiently analyze  pre-clinical drug combination therapies in cancer by

      integrating concepts in modern statistical and number-theoretic methods

      and pharmacology. 

      Role: Co-Investigator (15% effort).

1.4   09/30/2005-08/31/2007, R03 CA119758 (PI: Tan M), US$150,000

Division of Biostatistics, University of Maryland Greenebaum Cancer Center,

Baltimore, Maryland, USA

Title: Design and Analysis for Cancer Epidemiology Studies.

      This grant is to develop innovative statistical methods for addressing the difficult

      issues of multiplicity in current cancer etiology.

      Role: Co-Investigator (35% effort).

1.5   01/AUG/2009-01/JAN/2011, HKU Small Project Funding,

Account Code: 10400566.07227.25900.323.01

Project Code: 2009-0717-6166

Award (HK$): 66,667

Principal Investigator: Professor KW Ng

      Co-Investigator: Dr. GL TIAN

      Project Title: Further Properties and New Applications for the Family of Nested

                            Dirichlect Distributions

1.6   01/APR/2010-30/SEP/2011, HKU Seed Funding Program for Basic Research,

Account Code: 10400779.40058.25900.301.01

Project Code: 2009-1115-9042

Award (HK$): 120,000

      Principal Investigator: Dr. GL TIAN

      Project Title: Accelerating the Quadratic Lower-Bound (QLB) Algorithm via

                            Optimizing Shrinkage Parameter

1.7   01/NOV/2010-30/APR/2013 (Two Years and Six Months)

      Hong Kong RGC – General Research Fund 2010/2011 Exercise Year

      Panel: Biology & Medicine

      Account Code: 10500172.40058.25900.324.01

      Project Code: HKU 779210M

Award (HK$): 605,393 + 50,000

Principal Investigator: Dr. GL TIAN

      Project Title: New Non-randomized Response Techniques for Survey with Sensitive

                            Questions in the Epidemiological and Public Studies      

1.8   01/APR/2011-30/SEP/2012, HKU Seed Funding Program for Basic Research,

Account Code: 10401511.40058.25900.301.01

Project Code: 2010-1115-9010

Award (HK$): 58,000

      Principal Investigator: Dr. GL TIAN

      Project Title: A New Feature Selection Method for Generalized Linear Models with

                            Correlated Covariates

1.9   01/MAR/2012-28/FEB/2013, HKU Small Project Funding,

Account Code: 10401944.40058.25900.301.01

Project Code: 2011-0917-6166

Award (HK$): 36,800

      Principal Investigator: Dr. GL TIAN

      Project Title: Variable Selection via Least Absolute Deviation Regression with a

                            Diverging Number of Parameters

1.10   01/MAR/2013-28/FEB/2014, HKU Small Project Funding,

Account Code: 104002611.040058.25900.301.01

Project Code: 2012-0917-6071

Award (HK$): 69,575

      Principal Investigator: Dr. GL TIAN

      Project Title: G and Related Distributions with Applications in Reliability Growth Analysis

      Final Report Due Date: 28/05/2014

1.11   01/MAY/2014-30/OCT/2015, HKU Small Project Funding,

Account Code: 104002924.040058.25900.301.01

Project Code: 2013-0917-6038

Award (HK$): 64,343

      Principal Investigator: Dr. GL TIAN

      Project Title: A New MM Algorithm for Constrained Estimation in the

                            Proportional Hazards Model     

      Final Report Due Date: 28/05/2015         

1.12   01/MAR/2015-29/FEB/2016, HKU Small Project Funding,

Account Code: 104003745.040058.25900.301.01

Project Code: 2014-0917-6008

Award (HK$): 59,222

      Principal Investigator: Dr. GL TIAN

      Project Title: Poisson and Negative Binomial Item Count Techniques for Surveys

                            with Sensitive Question     

      Final Report Due Date: 29/05/2016


2. On-going in SUSTech


2.1  01/JAN/2018-31/DEC/2021, National Natural Science Foundation of China (No. 11771199),  面上项目

Award (RMB): 480,000

      Principal Investigator: Prof. GL TIAN

      Project Title: Studies of Several Topics in Minorization-Maximization (MM) Algorithms with Applications    


2.2  01/JAN/2019-31/DEC/2023, National Natural Science Foundation of China, Key Item (No. 4183000045), 重点项目

Award (RMB): 3,373,500

      Principal Investigator: Prof. Yan ZHENG, 南方科技大学环境科学与工程学院

      Co- Investigator: Prof. GL TIAN (Ranking No. 2 out of 15), 总人数15, 排名第二

      Project Title: Unraveling the Geological and Hydrogeochemical Factors Controlling the Spatial Heterogeneity of Groundwater Arsenic at Regional and Local Scales (中国北方地下水砷不同尺度空间非均质性驱动机制)



MPhil/PhD Students Supervised at UMBC and UMB

1. Miss Mathangi Gopalakrishnan, MS in Biostatistics, 2007. Secondary Supervisor; 

    Primary Supervisor: Professor Ming T. TAN (A joint MS biostatistics program between University of Maryland 

    at Baltimore County and University of Maryland at Baltimore).

    Thesis Title: Analyzing zero-inflated count data using non-iterative Bayesian sampling.


MPhil/PhD Students Supervised at HKU

2. Miss Huitian XUE, MPhil, 1/01/2010-31/12/2011, Secondary Supervisor; 

    Primary Supervisor: Professor KW NG.

    Thesis Title: Maximum likelihood estimation of parameters with constraints in normal and multinomial distributions 


3. Miss Xiqian DING, MPhil, 1/09/2012-30/11/2014, Sole Supervisor.

    Thesis Title: Some new statistical methods for a class of zero-truncated discrete distributions with applications 


4. Miss Yin LIU, PhD, 1/09/2011-31/08/2015, Sole Supervisor.

    Thesis Title: The generalization of the non-randomized parallel model and item count technique in surveys 

                        with sensitive questions

 

5. Mr. Da JU, PhD, 1/09/2012-31/08/2016, Secondary Supervisor; Primary Supervisor: Professor KC YUEN

    Thesis Title: Likelihood-based methods for constrained parameter problems


6. Miss Xaolin ZHENG, 1/09/2014-31/08/2016, Primary Supervisor; Secondary Supervisor: Dr. Philip LH YU

    Thesis Title: EM and MM algorithms for a class of left-truncated discrete models


7. Miss Chi ZHANG, PhD, 1/11/2013-31/10/2017, Primary Supervisor (1/11/2013-31/07/2016) and 

    Secondary Supervisor (1/08/2016-31/10/2017); Primary Supervisor: Professor KC YUEN (1/08/2016-31/10/2017).

    Thesis Title: Incomplete categorical data, inflated count data analyses and robust modeling with applications


8. Miss Xifen HUANG, PhD, 1/11/2014-31/10/2018, Supervisor (1/11/2014-31/07/2016) and 

    Secondary Supervisor (1/08/2016-31/10/2018); Primary Supervisor: Dr JF XU (1/08/2016-31/10/2018).

    Thesis Title: A unified minorization-maximization approach for fast and accurate estimation in high-dimensional 

                        parametric and semiparametric models

 

9. Mr. Fanghu DONG, Part-time PhD, 1/09/2011-31/08/2018, Supervisor.


MPhil/PhD Students Supervised at SUSTech

10. Mr. Pengyi LIU, PhD, 1/09/2017-31/08/2021, Primary Supervisor; Joint Primary Supervisor: 

      Professor KC YUEN [A joint PhD program between SUSTech and The University of Hong Kong]


11. Mr. Xiao KE, PhD, 1/09/2017-31/08/2020, Primary Supervisor; Joint Primary Supervisor: 

      Dr. TJ TONG [A joint PhD program between SUSTech and Hong Kong Baptist University]


12. Mr. Ruiwei ZHOU, MPhil, 1/09/2017-31/08/2019, Primary Supervisor 

      [A joint MPhil program between SUSTech and Harbin Institute of Technology (HIT)]


13. Miss Yuan SUN, PhD, 1/09/2018-31/08/2022, Primary Supervisor 

      [A joint MPhil program between SUSTech and HIT]


14. Mr. Jiaxin QIU, MPhil, 1/09/2018-31/08/2020, Primary Supervisor 

      [A joint MPhil program between SUSTech and HIT]


15. Mr. Xuzhi YANG, MPhil, 1/09/2018-31/08/2020, Primary Supervisor 

      [A joint MPhil program between SUSTech and HIT]


16. Miss Caifen LIU, MPhil, 1/09/2019-31/08/2020, Primary Supervisor 

      [A joint MPhil program between SUSTech and HIT]


17. Mr. Xuanyu LIU, MPhil, 1/09/2020-31/08/2022, Primary Supervisor, SUSTech


18. Miss Chaolin TIAN, MPhil, 1/09/2020-31/08/2022, Primary Supervisor, SUSTech


Teaching at HKU


Table 1: Student Evaluations on “Teacher Effectiveness” of mine

Course Code

Semester Offered

Number of Enrollment

My Average

Department Average

Dept Rang (100 Marks)

STAT2802/3902

Fall 2008

82

74.2

64.9

39.6 – 84.2

Fall 2009

66

78.8

67.9

44.8 – 87.2

Fall 2010

76

73.9

69.8

45.6 – 90.0

Fall 2011

52

64.0

71.4

43.1 – 88.2

Fall 2012

61

68.1

74.9

37.0 – 92.9

Fall 2013

105

68.2

74.8

55.0 – 97.5

Fall 2014

87

62.7

75.1 (UG)

55.6 –91.1 (UG)

STAT3317/6011

Spring 2009

10

78.8

66.7

37.5 – 89.7

Fall 2009

30

78.6

67.9

44.8 – 87.2

Fall 2010

38

71.2

69.8

45.6 – 90.0

Fall 2011

29

75.0

71.4

43.1 – 88.2

 

Fall 2012

43

84.2

74.9

37.0 – 92.9

Fall 2013

34

88.6

74.8

55.0 – 97.5

    Fall 2014

3 (UG)

83.3

75.1 (UG)

55.6 –91.1 (UG)

29(PG)

86.1

78.0 (PG)

55.6 –90.2 (PG)

STAT3304

Spring 2011

41

78.6

71.0

         42.2 – 90.8

Spring 2012

59

71.4

67.3

46.1 – 86.0

Spring 2013

57

72.2

72.2

42.6 – 88.6

STAT3331/3621

Spring 2015

26

83.8

75.1 (UG)

50.6 –97.5 (UG)

STAT2307

Spring 2009

16

*55.0

66.7

37.5 – 89.7

STAT7005

Fall 2013

17

*60.7

74.8

55.0 – 97.5

* It was my first time to teach STAT2307 and STAT7005


在香港大学统计与精算学系的教学经历

STAT2802/3902     Statistical Models

STAT3317/6011     Computational Statistics

STAT3304              Computer-aided Statistical Modeling

STAT3331/3621     Statistical Data Analysis

STAT2307              Statistics in Clinical Medicine and Bio-medical Research

STAT7005              Multivariate Methods


在南方科技大学数学系的教学经历

MAT7008/MA413   Advanced Statistics,         2016 Autumn Semester

MA204                    Mathematical Statistics,   2017, 2018, 2019 Spring Semester 

MAT7035                Computational Statistics, 2017, 2018, 2019 Autumn Semester


在南方科技大学数学系工作期间所编的教材 (Textbooks)

[1]  Tian GL, Jiang XJ and Liu Y (2019). Mathematical Statistics. Science Press, Beijing, P.R. China.







A. 3 Monographes



[1]  Tan M, Tian GL and Ng KW (2010). Bayesian Missing Data Problems: EM, Data Augmentation and Non-iterative Computation. Chapman & Hall/CRC (Biostatistics Series), Boca Raton, USA.


[2]  Ng KW, Tian GL and Tang ML (2011). Dirichlet and Related Distributions: Theory, Methods and Applications. John Wiley & Sons (Wiley Series in Probability and Statistics), New York, USA.


[3]  Tian GL and Tang ML (2014). Incomplete Categorical Data Design: Non-randomized Response Techniques for Sensitive Questions in Surveys.  Chapman & Hall/CRC (Statistics in the Social and Behavioral Sciences), Boca Raton, USA.




B.  107 Statistical Research Papers Published in Peer-Reviewed International Journals



Area 1: Multivariate zero-inflated count data analysis  (9 papers; Current Research Interest)


1.     Tian GL, Ding XQ, Liu Y* and Tang ML (2019). Some new statistical methods for a class of zero-truncated discrete distributions with applications. Computational Statistics, in press.

2.     Liu Y, Tian GL*, Tang ML and Yuen KC (2018). A new multivariate zero-adjusted Poisson model with applications to biomedicine. Biometrical Journal, in press.

3.     Tian GL, Liu Y*, Tang ML and Jiang XJ (2018). Type I multivariate zero-truncated / adjusted Poisson distributions with applications. Journal of Computational and applied Mathematics, 344, 132-153.

4.     Huang XF, Tian GL, Zhang C and Jiang XJ (2017). Type I multivariate zero-inflated generalized Poisson distribution with applications. Statistics and Its Interface 10(2), 291-311.

5.     Zhang C, Tian GL and Ng KW (2016). Properties of the zero-and-one-inflated Poisson distribution and likelihood-based inference methods. Statistics and Its Interface 9(1), 11-32.

6.    Ding XQ, JU D and Tian GL (2015). Multivariate zero-truncated/adjusted Charlier series distributions with applications. Journal of Statistical Distributions and Applications, Volume 2, Article 5, DOI: 10.1186/s40488-015-0029-5, http://www.jsdajournal.com/content/2/1/5

7.     Tian GL, Ma HJ, Zhou Y and Deng DL (2015). Generalized endpoint-inflated binomial model. Computational Statistics and Data Analysis 89, 97-114.

8.     Zhang C, Tian GL and Huang XF (2015). Two new bivariate zero-inflated generalized Poisson distributions with a flexible correlation structure. Statistics, Optimization and Information Computing 3, 105-137.

9.     Liu Y and Tian GL (2015). Type I multivariate zero-inflated Poisson distribution with applications. Computational Statistics and Data Analysis 83, 200-222.

 


Area 2: Incomplete categorical data analysis and EM/MM algorithms  (29 papers; Current Research Interest)


10.  Tian GL, Liu Y* and Tang ML (2019). A novel MM algorithm and the mode-sharing method in Bayesian computation for the analysis of general incomplete categorical data. Computational Statistics and Data Analysis, in press.

11.  Shan G, Hutson A, Wilding G, Ma CX and Tian GL (2019). Efficient statistical inference for a parallel study with missing data by using an exact method. Journal of Biopharmaceutical Statistics, in press.

12.  Zhuang TT, Tian GL and Ma CX* (2019). Homogeneity test of ratio of two proportions in stratified bilateral data. Statistics in Biopharmaceutical Research, in press.

13.  Shen X, Ma CX, Yuen KC and Tian GL* (2019). Common risk difference test and interval estimation of risk difference for stratified bilateral correlated data. Statistical Methods in Medical Research. in press.

14.  Huang XF, Xu JF* and Tian GL (2019). On profile MM algorithms for gamma frailty survival models.  Statistica Sinica, in press.

15.  Tian GL, Huang XF* and Xu JF (2019). An assembly and decomposition approach for constructing separable minorizing functions in a class of MM algorithms.  Statistica Sinica, in press.

16.  Jiang YL, Tian GL and Fei Y* (2019). A robust and efficient estimation method for partially nonlinear models via a new MM algorithm. Statistical Papers, in press.

17.  Zhuang TT, Tian GL and Ma CX* (2019). Confidence intervals for proportion ratios of stratified correlated bilateral data. Journal of Biopharmaceutical Statistics 29(1), 203-225.

18.  Li HQ, Tian GL, Tang NS and Cao HY* (2018). Assessing non-inferiority for incomplete paired-data under non-ignorable missing mechanism. Computational Statistics & Data Analysis 127, 69-81.

19.  Tian GL, JU D,Yuen KC and Zhang C* (2018). New expectation-maximization-type algorithms via stochastic representation for the analysis of truncated normal data with applications in biomedicine. Statistical Methods in Medical Research 27(8), 2459-2477.

20.  Li HQ, Tang NS, Tian GL, Cao HY* (2018). Testing the equality of risk difference among multiple incomplete two-way contingency tables. Statistics and Its Interface 11(2), 353-368.

21.  Tian GL, Zhang C* and Jiang XJ (2018). Valid statistical inference methods for a case control study with missing data. Statistical Methods in Medical Research 27(4), 1001–1023.

22.  Tian GL and Li HQ (2017). A new framework of statistical inferences based on the valid joint sampling distribution of observed counts in an incomplete contingency table. Statistical Methods in Medical Research 26(4), 1712–1736.

23.  Li HQ*, Tian GL, Jiang XJ and Tang NS (2016). Testing hypothesis for a simple ordering in incomplete contingency tables. Computational Statistics and Data Analysis 99, 25-37.

24.  Pei YB, Tian GL and Tang ML (2014). Testing homogeneity of proportion ratios for stratified correlated bilateral data in two-arm randomize clinical trials. Statistics in Medicine 33(25), 4370-4386.

25.  Li HQ, Chan ISF, Tang ML, Tian GL and Tang NS (2014). Confidence-interval construction for rate ratio in matched-pair studies with incomplete data. Journal of Biopharmaceutical Statistics 24(3), 546-568.

26.  Tang ML, He XJ and Tian GL (2013). A confidence interval approach for comparative studies involving binary outcomes in paired organs. Communication in Statistics: Simulation and Computation 42, 425–453.

27.  Tian GL, Tang ML and Liu CL (2012). Accelerating the quadratic lower-bound algorithm via optimizing the shrinkage parameter. Computational Statistics and Data Analysis 56(2), 255-265.

28.  Tang ML, Li HQ, Chan ISF and Tian GL (2011). On confidence interval construction for establishing equivalence of two binary-outcome treatments in matched-pair studies in the presence of incomplete data. Statistics in Biosciences 3(2), 223-249.

29.  Tang ML, Ling MH, Ling L and Tian GL (2010). Confidence intervals for a difference between proportions based on paired data. Statistics in Medicine 29(1), 86-96.

30.  Tian GL, Tang ML, Yuen KC and Ng KW (2010). Further properties and new applications for the nested Dirichlet distribution. Computational Statistics and Data Analysis 54, 394-405.

31.  Tang ML, Ling MH and Tian GL (2009). Exact and approximate unconditional confidence intervals for proportion difference in the presence of incomplete data. Statistics in Medicine 28, 625-641.

32.  Ng KW, Tang ML, Tian GL and Tan M (2009). The nested Dirichlet distribution and incomplete categorical data analysis. Statistica Sinica 19(1), 251-271.

33.  Ng KW, Tang ML, Tan M and Tian GL (2008). Grouped Dirichlet distribution: A new tool for incomplete categorical data analysis. Journal of Multivariate Analysis 99(3), 490-509. 

34.  Tang ML, Ng KW, Tian GL and Tan M (2007). On improved EM algorithm and confidence interval construction for incomplete r x c tables. Computational Statistics and Data Analysis 51(6), 2919-2933.

35.  Tan M, Fang HB, Tian GL and Wei G (2005). Testing multivariate normality in incomplete data of small sample size. Journal of Multivariate Analysis 93, 164-179.

36.  Tian GL, Ng KW and Geng Z (2003). Bayesian computation for contingency tables with incomplete cell-counts. Statistica Sinica 13(1), 189-206.

37.  Tan M, Fang HB, Tian GL and Houghton PJ (2002). Small-sample inference for incomplete longitudinal data with truncation and censoring in tumor xenograft models. Biometrics 58(3), 612-620.

38.  Fang KT, Geng Z and Tian GL (2000). Statistical inference for truncated Dirichlet distribution and its application in misclassification. Biometrical Journal 42(8), 1053-1068.


Area 3: Constrained parameter models and variable selection (21 papers)


39.  Wang MQ and Tian GL* (2018). Adaptive group lasso for high-dimensional generalized linear models. Statistical Papers, in press.

40.  Wu LC*, Tian GL, Zhang YQ and Ma T (2017). Variable selection in joint location, scale and skewness models with a skew-t-normal distribution. Statistics and Its Interface 10(2), 217-227.

41.  Wang MQ and Tian GL (2016). Robust group non-convex estimations for high-dimensional partially linear models. Journal of Nonparametric Statistics, 28(1), 49-67.

42.  Wu LC, Zhang ZZ, Tian GL and Xu DK (2016). A robust variable selection to t-type joint generalized linear models via penalized t-type pseudo-likelihood. Communications in Statistics - Simulation and Computation 45, 2320-2337.

43.  Miao R, Sun LQ and Tian GL (2016). Transformed linear quantile regression with censored survival data. Statistics and Its Interface 9(2), 131-139.

44.  Wang MQ, Song LX and Tian GL (2015). SCAD-penalized least absolute deviation regression in high-dimensional models. Communication in Statistics: Theory and Methods 44(12), 2452-2472.

45.  Ding JL, Tian GL and Yuen KC (2015). A new MM algorithm for constrained estimation in the proportional hazards model. Computational Statistics and Data Analysis 84, 135-151.

46.  Tian GL, Wang MQ and Song LX (2014). Variable selection in the high-dimensional continuous generalized linear model with current status data. Journal of Applied Statistics, 41(3), 467-483.

47.  Fang HB, Deng DL, Tian GL, Shen LX, Duan KM and Song JZ (2012). Analysis for temporal gene expressions under multiple biological conditions. Statistics in Biosciences 4(2), 282-299.  

48.  Zheng SR, Guo JH, Shi NZ and Tian GL (2012). Likelihood-based approaches for multivariate linear models under inequality restrictions for incomplete data. Journal of Statistical Planning and Inferences 142, 2926-2942.

49.  Tian GL, Ng KW and Yu PLH (2011). A note on the binomial model with simplex constraints. Computational Statistics and Data Analysis 55(12), 3381-3385.

50.  Gao W, Shi NZ, Tang ML, Fu LY and Tian GL (2010). Unified generalized iterative scaling and its applications. Computational Statistics and Data Analysis 54, 1066-1078.

51.  Liu ZQ, Chen DC, Tian GL, Tang ML, Tan M and Sheng L (2010). Efficient support vector machine method for survival prediction with SEER data. In Advances in Computational Biology (H.R. Arabnia, ed.), 11-18. Springer (Advances in Experimental Medicine and Biology 680), New York.

52.  Tian GL, Fang HB, Liu ZQ and Tan M (2009). Regularized (bridge) logistic regression for variable selection based on ROC criterion. Statistics and Its Interface, 2, 493-502.

53.  Tian GL, Ng KW and Tan M (2008). EM-type algorithms for computing restricted MLEs in multivariate normal distributions and multivariate t-distributions.        Computational Statistics and Data Analysis, 52(10), 4768-4778.  

54.   Tian GL, Tang ML, Fang HB and Tan M (2008). Efficient methods for estimating constrained parameters with applications to regularized (lasso) logistic regression.     Computational Statistics and Data Analysis 52(7), 3528-3542.

55.  Tan M, Tian GL, Fang HB and Ng KW (2007). A fast EM algorithm for quadratic optimization subject to convex constraints. Statistica Sinica 17(3), 945-964.

56.  Liu ZQ, Jiang F, Tian GL, Wang S, Sato F, Meltzer SJ and Tan M (2007). Sparse logistic regression with L_p penalty for biomarker identification. Statistical Applications in Genetics and Molecular Biology 6(1), Article 6.

57.  Fang HB, Tian GL, Xiong XP and Tan M (2006). A multivariate random-effects model with restricted parameters: Application to assessing radiation therapy for brain tumors.  Statistics in Medicine 25(11), 1948-1959.   

58.  Tan M, Fang HB, Tian GL and Houghton PJ (2005). Repeated-measures models with constrained parameters for incomplete data in tumor xenograft experiments. Statistics in Medicine 24(1), 109-119.

59.  Tan M, Tian GL and Fang HB (2003). Estimating restricted normal means using the EM-type algorithms and IBF sampling. In Development of Modern Statistics and Related Topics - In Celebration of Professor Yaoting Zhang's 70th Birthday (J. Huang and H. Zhang, eds.), 53-73. World Scientific Publishing Co. Inc., New Jersey.


Area 4: Sample surveys with sensitive questions (17 papers)


60.  Tian GL, Liu Y* and Tang ML (2019). Logistic regression analysis of non-randomized response data collected by the parallel model in sensitive surveys. Australian & New Zealand Journal of Statistics, in press.

61.  Liu Y and Tian GL* (2018). Advances of the non-randomized response techniques in sample surveys with sensitive questions. Chinese Journal of Applied Probability and Statistics, in press.

62.  Liu Y, Tian GL*, Wu Q and Tang ML (2018). Poisson-Poisson item count techniques for surveys with sensitive qualitative data. Statistical Papers, in press.

63.  Tian GL, Tang ML, Wu Q and Liu Y (2017). Poisson and negative binomial item count techniques for surveys with sensitive question. Statistical Methods in Medical Research 26(2), 931–947.

64.  Huang XF, Tian GL, Liu Y and Yu JW (2015). Type II combination questionnaire model: A new survey design for a totally sensitive binary variable correlated with another non-sensitive binary variable. Journal of the Korean Statistical Society 44(3), 432-447.

65.  Tian GL (2014). A new non-randomized response model: The parallel model. Statistica Neerlandica 68(4), 293-323.

66.  Tang ML, Wu Q, Tian GL and Guo JH (2014). Two-sample non-randomized response techniques for sensitive questions. Communication in Statistics: Theory and Methods 43(2), 408-425.

67.  Liu Y and Tian GL (2014). Sample size determination for the parallel model in a survey with sensitive questions. Journal of the Korean Statistical Society 43, 235-249.

68.  Liu Y and Tian GL (2013b). A variant of the parallel model for sample surveys with sensitive characteristics. Computational Statistics and Data Analysis 67, 115-135.

69.  Liu Y and Tian GL (2013a). Multi-category parallel models in the design of surveys with sensitive questions. Statistics and Its Interface 6(1), 137-149.

70.  Yu JW, Lu Y and Tian GL (2013).  A survey design for a sensitive binary variable correlated with another non-sensitive binary variable. Journal of Probability and Statistics, Volume 2013, Article ID 827048, 11 pages, http://dx.doi.org/10.1155/2013/827048.

71.  Tian GL, Tang ML, Liu ZQ, Tan M and Tang NS (2011). Sample size determination for the non-randomized triangular model for sensitive questions in a survey. Statistical Methods in Medical Research 20(3), 159-173.

72.  Tang ML, Tian GL, Tang NS and Liu ZQ (2009). A new non-randomized multi-category response model for surveys with a single sensitive question: Design and analysis. Journal of the Korean Statistical Society 38, 339-349.

73.  Tan M, Tian GL and Tang ML (2009). Sample surveys with sensitive questions: A non-randomized response approach. The American Statistician 63(1), 9-16.

74.  Tian GL, Yuen KC, Tang ML and Tan M (2009). Bayesian non-randomized response models for surveys with sensitive questions. Statistics and Its Interface 2, 13-25.

75.  Yu JW, Tian GL and Tang ML (2008). Two new models for survey sampling with sensitive characteristic: Design and analysis. Metrika 67(3), 251-263.  

76.  Tian GL, Yu JW, Tang ML and Geng Z (2007). A new non-randomized model for analyzing sensitive questions with binary outcomes. Statistics in Medicine 26(23), 4238-4252.


Area 5: Reliability and prediction inferences (4 papers)


77.  Tian GL, Ou ZJ, Zhang C and Ng KW (2016). G and related distributions with applications in reliability growth analysis. Statistics and Its Interface 9(3), 315-332.

78.  Tian GL, Tang ML and Yu JW (2011). Bayesian estimation and prediction for the power law process with left-truncated data. Journal of Data Science 9(3), 445-470.

79.  Yu JW, Tian GL and Tang ML (2008). Statistical inference and prediction for the Weibull process with incomplete observations. Computational Statistics and Data Analysis 52(3), 1587-1603.

80.  Yu JW, Tian GL and Tang ML (2007). Predictive analyses for non-homogeneous Poisson processes with power law using Bayesian approach. Computational Statistics and Data Analysis 51(9), 4254-4268.


Area 6: Experimental design for drug combination studies (6 papers)


81.  Tan M, Fang HB and Tian GL (2009). Dose and sample size determination for multi-drug combination studies. Statistics in Biopharmaceutical Research 1(3), 301-316.

82.  Fang HB, Tian GL, Li W and Tan M (2009). Design and sample size for evaluating combinations of drugs of linear and log-linear dose-response curves. Journal of Biopharmaceutical Statistics 19(4), 625-640.

83.  Tian GL, Fang HB, Tan M, Qin H and Tang ML (2009). Uniform distributions in a class of convex polyhedrons with applications to drug combination studies. Journal of Multivariate Analysis 100(8), 1854-1865.

84.  Tan M, Fang HB and Tian GL (2005). Statistical analysis for tumor xenograft experiments in drug development. In Contemporary Multivariate Analysis and Experimental Designs - In Celebration of Professor Kai-Tai Fang's 65th Birthday (J. Fan and G. Li, eds.), 351-368. World Scientific Publishing Co. Inc., New Jersey.

85.  Fang HB, Tian GL and Tan M (2004). Hierarchical models for tumor xenograft experiments in drug development.  Journal of Biopharmaceutical Statistics 14(4), 931-945.

86.  Tan M, Fang HB, Tian GL and Houghton PJ (2003). Experimental design and sample size determination for testing synergism in drug combination studies based on uniform measures. Statistics in Medicine 22(13), 2091-2100.


Area 7: Cancer clinical trial and design (3 papers)


87.  Lin W, Voskens CJ, Zhang XY, Schindler DG, Wood A, Burch E, Wei YD, Chen LP, Tian GL, Tamada K, Wang LX, Schulze DH, Mann D, Strome SE (2008). Fc dependent expression of CD137 on human NK cells: insights into “agonistic” effects of anti-CD137 monoclonal antibodies. Blood 112(3), 699-707.

88.  Khanna N, Mishra SI, Tian GL, Tan M, Arnold S, Lee C, Ramachandran S, Bell L, Baquet C and Lorincz A (2007). Human papillomavirus detection in self-collected vaginal specimens and matched clinician-collected cervical specimens. International Journal of Gynecological Cancer 17, 615-622.

89.  Williams R, Olivi S, Mackert P, Fletcher L, Tian GL and Wang W (2002). Comparison of energy prediction equations with measured resting energy expenditure in children with sickle cell anemia. Journal of the American Dietetic Association 102(7), 956-961.


Area 8: Non-iterative Bayesian methods (7 papers)


90.  Tian GL, Ng KW, Li KC, and Tan M (2009). Non-iterative sampling-based Bayesian methods for identifying changepoints in the sequence of cases of haemolytic uraemic syndrome. Computational Statistics and Data Analysis 53(9), 3314-3323.

91.  Tian GL, Tan M and Ng KW (2007). An exact non-iterative sampling procedure for discrete missing data problems. Statistica Neerlandica 61(2), 232-242.

92.  Tan M, Tian GL and Fang HB (2007). An Efficient MCEM algorithm for fitting generalized linear mixed models for correlated binary data. Journal of Statistical Computation and Simulation 77(11), 929-943.

93.  Tan M, Tian GL and Ng KW (2006). Hierarchical models for repeated binary data using the IBF sampler. Computational Statistics and Data Analysis 50(5), 1272-1286.

94.  Tan M, Tian GL and Ng KW (2003). A non-iterative sampling method for computing posteriors in the structure of EM-type algorithms. Statistica Sinica 13(3), 625-639.

95.  Tian GL and Tan M (2003). Exact statistical solutions using the inverse Bayes formulae. Statistics & Probability Letters 62(3), 305-315.

96.  Tan M, Tian GL and Xiong XP (2001). Explicit Bayesian solution for incomplete pre-post test problems using inverse Bayes formulae. Communications in Statistics - Theory and Methods 30(6), 1111-1129.


Area 9: Multivariate analysis (11 papers)


97.  Liang JJ, Ng KW and Tian GL (2018). A class of uniform tests for goodness-of-fit of the multivariate L_p-norm spherical distributions and the l_p-norm symmetric distributions. Annals of the Institute of Statistical Mathematics, in press.

98.  Zhang YQ, Tian GL and Tang NS (2016). Latent variable selection in structural equation models. Journal of Multivariate Analysis 152, 190-205.

99.  Liang JJ, Ng KW and Tian GL (2016). A stochastic representation for the lp-norm symmetric distribution and its applications. Communications in Statistics - Simulation and Computation, in press.

100.  Liu BS, Xu L, Zheng SR and Tian GL (2014). A new test for the proportionality of two large-dimensional covariance matrices. Journal of Multivariate Analysis 131, 293-308.

101. Yin ZH, Gao W, Tang ML and Tian GL (2013). Estimation of non-parametric regression models with a mixture of Berkson and classical errors. Statistics and Probability Letters 83, 1151-1162.

102. Yu JW and Tian GL (2011). Efficient algorithms for generating truncated multivariate normal distributions. Acta Mathematica Applicatae Sinica (English Series) 27(4), 601-612.

103. Tian GL, Tan M, Ng KW and Tang ML (2009). A unified method for checking compatibility and uniqueness for finite discrete conditional distributions. Communication in Statistics: Theory and Methods 38(1), 115-129.

104. Ng KW and Tian GL (2001). Characteristic functions of L1-spherical and L1-norm symmetric distributions and their applications. Journal of Multivariate Analysis 76(2), 192-213.

105. Fang KT, Tian GL and Xie MY (1999). Uniform design over a convex polyhedron. Chinese Science Bulletin 44(2), 112-114.

106. Tian GL and Fang KT (1999). Uniform designs for mixture-amount experiments and for mixture experiments under order restrictions. Science in China Series A: Mathematics 42(5), 456-470.

107.  Tian GL (1998). The comparison between polynomial regression and orthogonal polynomial regression.  Statistics & Probability Letters 38, 289-294.




C.  34 Statistical Research Papers Published in Peer-Reviewed Chinese Journals



1)  Liu HX and Tian GL (2003). Statistical analysis of multiple Weibull processes with unequal scale parameters. Training and Research Journal of Hubei University of Edication 20(5), 1-6.

2)  Liu HX and Tian GL (2003). On the estimation methods of parameters for AMSAA model. Training and Research Journal of Hubei University of Edication, 20(2), 4-9.

3)  Liu HX and Tian GL (2003). Statistical inference for the achieved MTBF of Weibull process. Journal of Hubei University (Natural Science Edition) 25(3), 202-208.

4) Tian GL (1993). Improved approximate classical limits of reliable life for normal distributions. Structure and Environment Engineering 3, 30-33.

5)  Tian GL (1993). Bayes statistical inference procedures for multi-system Weibull process. Structure and Environment Engineering 1, 1-8.

6)  Tian GL (1993). Prediction techniques in sampling tests of aerial products. Aviation Reliability Engineering Letters 1, 8-17.

7)  Tian GL (1992). Prediction techniques and their applications in sampling tests.  The sixth Proceeding of Chinese Electronics Association, 16-22. Guiyang.

8)  Tian GL (1992). Bayesian analysis approach of reliability growth for exponential distribution in the case of measuring of fix time interval. Journal of System Engineering and Electronics 10, 72-80.

9)  Tian GL (1992). Statistical analysis methods for reliability growth models at last stage. Structure and Environment Engineering 2, 35-45.

10) Tian GL (1992). Bayesian prediction intervals of the k-th future failure time for a Weibull process. Applied Mathematics---A Journal of Chinese Universities 2, 264-271.

11) Tian GL (1992). Bayesian limits for environment factor. Journal of Astronautics 2, 34-40.

12) Tian GL (1992). Reliability growth models for binomial distributions. Journal of Astronautics 1, 55-61.

13) Fang LY, Wu JJ and Tian GL (1991). A method to determine the damping rate from the decay-beat wave with nonlinear characteristics. Journal of Astronautics 4, 77-82.

14) Tian GL (1991). Reliability growth prediction models for binomial distribution. Structure and Environment Engineering 4, 17-25.

15) Tian GL (1991). Duane model and AMSAA models with grouping and missing data: A Bayesian analysis approach. Journal of System Engineering and Electronics 7, 46-54.

16) Tian GL (1991). An estimation method for parameters with applications to reliability growth analysis. Journal of System Engineering and Electronics 4, 58-64.

17) Tian GL (1991). Accelerated life testing-constant-stress for Weibull process (II). Structure and Environment Engineering 2, 47-53.

18) Tian GL (1991). Accelerated life testing-constant-stress for Weibull process (I). Structure and Environment Engineering 1, 18-24.

19) Tian GL (1990). Reliability assessment for trinomial distribution model. Journal of System Engineering and Electronics 12, 76-80.

20) Tian GL (1990). Comparison of test data for repairable systems. Structure and Environment Engineering 4, 18-25.

21) Tian GL (1990). Classical approximate limits of environment factor for success-failure products.  Journal of System Engineering and Electronics 10, 61-68.

22) Tian GL (1990). Analysis method of AMSAA model for grouped data. Structure and Environment Engineering 3, 1-8.

23) Tian GL (1990). Reliability growth model for Poisson process (III) --- Assessment and prediction. Journal of System Engineering and Electronics 8, 70-76.

24) Tian GL (1990). Reliability growth model for Poisson process (II) --- In the case of time-truncated testing. Journal of System Engineering and Electronics 7, 72-76.

25) Tian GL (1990). Reliability growth model for Poisson process (I) --- In the case of failure-truncated testing. Journal of System Engineering and Electronics 6, 62-67.

26) Tian GL (1990). Statistical analysis of testing data for repairable systems---predicting and testing for outlier in Weibull process. Mathematical Statistics and Applied Probability 5(3), 355-365.

27) Tian GL (1990). The classical analysis approach of reliability growth for negative binomial distribution. Structure and Environment Engineering 1, 28-33.

28) Tian GL (1989). Classical confidence limits for MTBF of Duane model. Journal of System Engineering and Electronics 8, 72-75.

29) Tian GL and Liu ZX (1989). Classical limits for the environment factor of negative binomial distribution. Structure and Environment Engineering 6, 16-23.

30) Tian GL (1989). Analysis method for reliability growth of Gompertz model. Structure and Environment Engineering 5, 22-29.

31) Tian GL (1989). Interval estimation for the structure reliability of normal distribution. Structure and Environment Engineering 4, 46-49.

32) Tian GL (1989). Interval estimates for the failure rate of normal distribution. Structure and Environment Engineering 3, 50-53.

33) Tian GL (1989). Hypothesis testing of shape parameter for multi-system Weibull process. Structure and Environment Engineering 2, 41-46.

34) Tian GL (1989). Classical analysis method for determining the growth of MTBF of electronic product. Structure and Environment Engineering 1, 1-5.