TIAN, Guoliang
Personal Page:http://faculty.sustc.edu.cn/profiles/tiangl/en
Brief Biography:
Guo-Liang Tian, Ph.D., is a Full Professor of Statistics at Department of Statistics and Data Science of Southern University of Science and Technology (SUSTech). He was an Associate Professor of Statistics at Department of Statistics and Actuarial Science of the University of Hong Kong. He was a senior bio-statistician at the University of Maryland Marlene and Stewart Greenebaum Comprehensive Cancer Center (Baltimore, Maryland, USA) from 2002 to 2008, a Postdoctoral Research Associate at Department of Biostatistics, St. Jude Children's Research Hospital (Memphis, Tennessee, USA) from 2000 to 2002, and a Postdoctoral Fellowship at Department of Probability and Statistics, Peking University (Beijing, P.R. China) from 1998 to 2000. He earned his Ph.D. in statistics in 1998 from the Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing. He obtained his Master of Statistics in 1988 from Wuhan University. He was an Elected Member of International Statistics Institute. His current research interests include biostatistics, computational statistics and social statistics. He was the author of 14 top tier biostatistics papers and more than 90 other statistics papers in peer-reviewed international academic journals.
Research Interests:
Biostatistics: Multivariate zero-inflated count data analysis, Skewed and asymmetric continuous data analysis, Continuous proportional and compositional data analysis
Computational Statistics: EM algorithm, MM algorithm
Social Statistics: Sample surveys with sensitive questions
Professional Experience:
2019.08.22 – Present, Professor. Department of Statistics and Data Science, Southern University of Science and Technology (SUSTech)
2016.08.01 – 2019.08.21, Professor. Department of Mathematics, SUSTech
2008.09.01 – 2016.07.31, Associate Professor. Department of Statistics and Actuarial Science, The University of Hong Kong
2002.07.01 – 2008.08.31, Senior Biostatistician. Division of Biostatistics, University of Maryland, Marlene and Stewart Greenebaum Comprehensive Cancer Center, Baltimore, MD, USA
2002.07.01 – 2008.08.31, Instructor. Department of Epidemiology and Preventive Medicine, University of Maryland, School of Medicine, Baltimore, MD, USA
2000.05.01 – 2002.06.30, Postdoctoral Research Associate. Partner: Prof. Ming TAN. Department of Biostatistics, St. Jude Children's Research Hospital, Memphis, Tennessee, USA
1998.09.01 – 2000.04.30, Postdoctoral Fellowship. Partner: Prof. Zhi GENG. Department of Probability and Statistics, Peking University, Beijing
1988.08.01 – 1995.08.31,Senior Engineer (Engineer, Assistant Engineer). Chinese Academy of Air Vehicle, The Ministry of Aerospace Industry, Beijing
Educational Background:
1995.9 – 1998.7 Ph.D., Statistics. Institute of Applied Mathematics, Chinese Academy of Sciences, Beijing, China
1985.9 – 1988.7 M.Sc., Statistics. Wuhan University, Wuhan, Hubei Province, P. R. China
1981.9 – 1985.7 B.Sc., Mathematics. Hunan Normal University, Changsha, Hunan Province, P. R. China.
Honor and Awards:
Peacock Plan Award (Tier B), Shenzhen, 2017
Professional Memberships:
2000.5 – Present Member, American Statistical Association
2000.5 – Present Permanent Member, International Chinese Statistical Association
2014.6 – Present Elected member, International Statistical Institute (ISI)
Professional Service:
Associate Editor, Statistics and Its Interface, 2013 – Present
Associate Editor, Communications in Statistics - Theory and Methods, 2013 – Present
Associate Editor, Communications in Statistics - Simulation and Computation, 2013 --– Present
Associate Editor, Computational Statistics and Data Analysis, 2014 – Present
Selected Publications:
Statistical Methods in Medical Research [Impact Factor=4.472; Ranking No. 1 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (6 papers)
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, 28(8), 2418-2438.
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.
Tian GL, Zhang C* and Jiang XJ (2018). Valid statistical inference methods for a case-control study with missing data, 27(4), 1001–1023.
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.
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.
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.
Statistics in Medicine [Impact Factor=1.825; Ranking No. 3 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (7 papers)
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.
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.
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.
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.
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.
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.
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.
Biometrics [Impact Factor=1.568; Ranking No. 4 in the category of biostatistics, 2014 JCR, ISI Web Knowledge] (1 paper)
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.
Statistica Sinica (6 papers)
Tian GL, Huang XF* and Xu JF (2019). An assembly and decomposition approach for constructing separable minorizing functions in a class of MM algorithms, 29, 961-982.
Huang XF, Xu JF* and Tian GL (2019). On profile MM algorithms for gamma frailty survival models, 29, 895-916.
Ng KW, Tang ML, Tian GL and Tan M (2009). The nested Dirichlet distribution and incomplete categorical data analysis, 19(1), 251-271.
Tan M, Tian GL, Fang HB and Ng KW (2007). A fast EM algorithm for quadratic optimization subject to convex constraints, 17(3), 945-964.
Tan M, Tian GL and Ng KW (2003). A non-iterative sampling method for computing posteriors in the structure of EM-type algorithms, 13(3), 625-639.
Tian GL, Ng KW and Geng Z (2003). Bayesian computation for contingency tables with incomplete cell-counts, 13(1), 189-206.
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)
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),
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),
Award (RMB): 3,373,500
Principal Investigator: Prof. Yan ZHENG, School of Environmental Science & Engineering at SUSTech
Co- Investigator: Prof. GL TIAN (Ranking No. 2 out of 15)
Project Title: Unraveling the Geological and Hydrogeochemical Factors Controlling the Spatial Heterogeneity of Groundwater Arsenic at Regional and Local Scales
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
MPhil/PhD Students Supervised at SUSTech
9. 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]
10. 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]
11. Mr. Ruiwei ZHOU, MPhil, 1/09/2017-31/08/2019, Primary Supervisor [A joint MPhil program between SUSTech and Harbin Institute of Technology (HIT)]
12. Miss Yuan SUN, PhD, 1/09/2018-31/08/2022, Primary Supervisor [A joint MPhil program between SUSTech and HIT]
13. Mr. Jiaxin QIU, MPhil, 1/09/2018-31/08/2020, Primary Supervisor [A joint MPhil program between SUSTech and HIT]
14. Mr. Xuzhi YANG, MPhil, 1/09/2018-31/08/2020, Primary Supervisor [A joint MPhil program between SUSTech and HIT]
15. Miss Caifen LIU, MPhil, 1/09/2019-31/08/2020, Primary Supervisor [A joint MPhil program between SUSTech and HIT]
16. Mr. Xunjian LI, PhD, 1/09/2019-31/08/2023, Primary Supervisor, SUSTech
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
19. Mr. Yonggui ZHOU, MPhil, 1/09/2019-31/08/2021, Primary Supervisor, SUSTech
Teaching at HKU
Teaching Experience at the Department of Statistics and Actuarial Science of HKU
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
Teaching Experience at the Department of Mathematics of SUSTech
MAT7008/MA413 Advanced Statistics, 2016 Autumn Semester
MA204 Mathematical Statistics, 2017, 2018, 2019 Spring Semester
MAT7035 Computational Statistics, 2017, 2018, 2019 Autumn Semester
Textbooks Completed during Working at the Department of Mathematics of SUSTech
Tian GL, Jiang XJ and Liu Y (2019). Mathematical Statistics. Science Press, Beijing, P.R. China.
· Area 1: Multivariate zero-inflated count data analysis
(10 papers; Current Research Interest)
1. Zhang C, Tian GL, Yuen KC, Wu Q and Li T* (2020). Multivariate zero-and-one inflated Poisson model with applications. Journal of Computational and Applied Mathematics 365, Article: 112356.
2. Liu Y, Tian GL*, Tang ML and Yuen KC (2019). A new multivariate zero-adjusted Poisson model with applications to biomedicine. Biometrical Journal 61, 1340-1370.
3. 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 34, 1393-1426.
4. 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.
5. 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.
6. 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.
7. 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
8. Tian GL, Ma HJ, Zhou Y and Deng DL (2015). Generalized endpoint-inflated binomial model. Computational Statistics and Data Analysis 89, 97-114.
9. 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.
10. 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: Continuous proportional and compositional data analysis
(1 paper; Current Research Interest)
11. Liu PY, Yuen KC, Wu LC, Tian GL and LI T* (2020). Zero-one-inflated simplex regression models for the analysis of continuous proportion data. Statistics and Its Interface, in press.
· Area 3: Incomplete categorical data analysis and EM/MM algorithms
(30 papers; Current Research Interest)
12. Zhang C, Tang ML, Li T, Sun Y, Tian GL* (2020). A new multivariate Laplace distribution based on the mixture of normal distributions (in Chinese). Sci Sin Math, in press.
13. Tian GL, Liu Y*, Tang ML and Li T (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 140, 122-143.
14. 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 29(3), 478-490.
15. 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.
16. 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 28(8), 2418-2438.
17. Zhuang TT, Tian GL and Ma CX* (2019). Homogeneity test of ratio of two proportions in stratified bilateral data. Statistics in Biopharmaceutical Research 11(3), 200-209.
19. 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 29, 961-982.
20. 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.
21. 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.
22. 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.
23. 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.
24. 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.
25. 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.
26. 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.
27. 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.
28. 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.
29. 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.
30. 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.
31. 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.
32. 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.
33. 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.
34. 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.
35. 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.
36. 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.
37. 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.
38. 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.
39. Tian GL, Ng KW and Geng Z (2003). Bayesian computation for contingency tables with incomplete cell-counts. Statistica Sinica 13(1), 189-206.
40. 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.
41. 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.