2024


1. Lu Qin, Shishun Zhao, Wenlai Guo, Tiejun Tong and Ke Yang (2024)
   A comparison of two models for detecting inconsistency in network meta-analysis
   Research Synthesis Methods, in press.
   
   
2. Zhijian Li, Tiejun Tong and Yuedong Wang (2024)
   A difference-based method for testing no effect in nonparametric regression
   Computational Statistics, in press.
   
   
3. Jiajin Wei, Ping He and Tiejun Tong (2024)
   Estimating the reciprocal of a binomial proportion
   International Statistical Review, 92: 1-16.
   
   
4. Yuejin Zhou, Wenwu Wang, Tao Hu, Tiejun Tong and Zhonghua Liu (2024)
   Causal mediation analysis for an ordinal outcome with multiple mediators
   Structural Equation Modeling: A Multidisciplinary Journal, 31: 205-216.
   
   
5. Zongliang Hu, Tiejun Tong and Marc. G. Genton (2024)
   A pairwise Hotelling method for testing high-dimensional mean vectors
   Statistica Sinica, 34: 229-256.
   
   
6. Wenchao Xu, Hongmei Lin, Tiejun Tong and Riquan Zhang (2024)
   A new method for estimating Sharpe ratio function via local maximum likelihood
   Journal of Applied Statistics, 51: 34-52.
   
   

2023


7. Jiandong Shi, Dehui Luo, Xiang Wan, Yue Liu, Jiming Liu, Zhaoxiang Bian and Tiejun Tong (2023)
   Detecting the skewness of data from the five-number summary and its application in meta-analysis
   Statistical Methods in Medical Research, 32: 1338–1360.
   
        [Online Calculator]
   
   -- This paper has been recognized as a Highly Cited Paper in ISI Web of Science, with a total of 35 citations (and 60+ citations in Google Scholar) as of August 2024.
   
   
   
8. Zongliang Hu, Yiping Yang, Gaorong Li and Tiejun Tong (2023)
   Regularized t distribution: definition, properties and applications
   Scandinavian Journal of Statistics, 50: 1884-1900.
   
   
9. Wenwu Wang, Ping Yu, Yuejin Zhou, Tiejun Tong and Zhonghua Liu (2023)
   Equivalence of two least-squares estimators for indirect effects
   Current Psychology, 42: 7364–7375.
   
   

2022


10. Sanying Feng, Menghan Zhang and Tiejun Tong (2022)
    Variable selection for functional linear models with strong heredity constraint
    Annals of the Institute of Statistical Mathematics, 74: 321–339.
    
    
11. Yanyan Ouyang, Jiamin Liu, Tiejun Tong and Wangli Xu (2022)
    A rank-based high-dimensional test for equality of mean vectors
    Computational Statistics and Data Analysis, 173: 107495.
    
    
12. Hongmei Lin, Tiejun Tong, Yuedong Wang, Wenchao Xu and Riquan Zhang (2022)
    Direct local linear estimation for Sharpe ratio function
    Canadian Journal of Statistics, 50: 36-58.
    
    
13. Wenwu Wang, Jun Lu, Tiejun Tong and Zhonghua Liu (2022)
    Debiased learning and forecasting of first derivative
    Knowledge-Based Systems, 236: 107781.
    
    
14. Yan Zhou, Minjiao Peng, Bin Yang, Tiejun Tong, Baoxue Zhang and Niansheng Tang (2022)
    scDLC: a deep learning framework to classify large sample single-cell RNA-seq data
    BMC Genomics, 23: 504.
    
    

2021


15. Jiajin Wei, Enxuan Lin, Jiandong Shi, Ke Yang, Zongliang Hu, Xian-Tao Zeng and Tiejun Tong (2021)
    Meta-analysis with zero-event studies: a comparative study with application to COVID-19 data
    Military Medical Research, 8: 41.
    
    
16. Wenhao Cao, Lianne Siegel, Jincheng Zhou, Motao Zhu, Tiejun Tong, Yong Chen and Haitao Chu (2021)
    Estimating the reference interval from a fixed effects meta-analysis
    Research Synthesis Methods, 12: 630-640.
    
    
17. Sanying Feng, Gaorong Li, Heng Peng and Tiejun Tong (2021)
    Varying coefficient panel data model with interactive fixed effects
    Statistica Sinica, 31: 935-957.
    
    
18. Zongliang Hu, Zhishui Hu, Kai Dong, Tiejun Tong and Yuedong Wang (2021)
    A shrinkage approach to joint estimation of multiple covariance matrices
    Metrika, 84: 339-374.
    
    
19. Zongliang Hu, Yan Zhou and Tiejun Tong (2021)
    Meta-analyzing multiple omics data with robust variable selection
    Frontiers in Genetics, 12: 656826.
    
    
20. Wenwu Wang, Wei Shen and Tiejun Tong (2021)
    Robust estimation of nonparametric function via addition sequence
    Journal of Statistical Planning and Inference, 211: 423-438.
    
    

2020


21. Jiandong Shi, Dehui Luo, Hong Weng, Xian-Tao Zeng, Lu Lin, Haitao Chu and Tiejun Tong (2020)
    Optimally estimating the sample standard deviation from the five-number summary
    Research Synthesis Methods, 11: 641-654.
    
         [Online Calculator]
    
    -- 基于中位数的荟萃分析新发展  【科学观察, 16(6): 82-84, 2021, 中国数学研究热点论文特约稿】
    
    
    -- This paper has been recognized as a Highly Cited Paper (and a Hot Paper in 2022) in ISI Web of Science, with a total of 250 citations (and 300+ citations in Google Scholar) as of August 2024. This paper has also been recognized as a Top Cited Paper in Research Synthesis Methods among all the papers published between 1 January 2020 and 31 December 2021.
    
    
    
22. Hong Zhang, Tiejun Tong, John Landers and Zheyang Wu (2020)
    TFisher: A powerful truncation and weighting procedure for combining p-values
    Annals of Applied Statistics, 14: 178-201.
    
    
23. Fengyang He, Huixia Judy Wang and Tiejun Tong (2020)
    Extremal linear quantile regression with Weibull-type tails
    Statistica Sinica, 30: 1357-1377.
    
    
24. Hailun Wang, Pak Sham, Tiejun Tong and Herbert Pang (2020)
    Pathway-based single-cell RNA-Seq classification and construction of co-occurrence network using random forests
    IEEE Journal of Biomedical and Health Informatics, 24: 1814-1822.
    
    
25. Shuwei Li, Tao Hu, Tiejun Tong and Jianguo Sun (2020)
    Semi-parametric regression analysis of multivariate doubly-censored data
    Statistical Modelling, 20: 502-526.
    
    
26. Ke Yang, Hiu-Yee Kwan, Zhiling Yu and Tiejun Tong (2020)
    Model selection between the fixed-effects model and the random-effects model in meta-analysis
    Statistics and Its Interface (Special Issue on Meta-Analysis), 13: 501-510.
    
    
27. Jiandong Shi, Tiejun Tong, Yuedong Wang and Marc G. Genton (2020)
    Estimating the mean and variance from the five-number summary of a log-normal distribution
    Statistics and Its Interface (Special Issue on Meta-Analysis), 13: 519-531.
    
    

2019


28. Wenwu Wang, Ping Yu, Lu Lin and Tiejun Tong (2019)
    Robust estimation of derivatives using locally weighted least absolute deviation regression
    Journal of Machine Learning Research, 20(60): 1−49.
    
    
29. Zongliang Hu, Tiejun Tong and Marc G. Genton (2019)
    Diagonal likelihood ratio test for equality of mean vectors in high-dimensional data
    Biometrics, 75: 256-267.
    
    
30. Yiping Yang, Tiejun Tong and Gaorong Li (2019)
    SIMEX estimation for single-index model with covariate measurement error
    AStA Advances in Statistical Analysis, 103: 137-161.
    
    
31. Yan Zhou, Jiadi Zhu, Tiejun Tong, Junhui Wang, Bingqing Lin and Jun Zhang (2019)
    A statistical normalization method and differential expression analysis for RNA-seq data between different species
    BMC Bioinformatics, 20: 163.
    
    

2018


32. Dehui Luo, Xiang Wan, Jiming Liu and Tiejun Tong (2018)
    Optimally estimating the sample mean from the sample size, median, mid-range and/or mid-quartile range
    Statistical Methods in Medical Research, 27: 1785-1805.
    
         [Online Calculator]
    
    -- 中国热点论文榜  【科学观察, 18(6): 1-12, 2023】
    
    -- 中国热点论文榜  【科学观察, 17(6): 1-12, 2022】
    
    -- 童铁军团队"样本均值优化算法"一文引用内容分析  【科学观察, 16(6): 90-98, 2021】
    
    -- 如何实现从样本量、中位数、极值或四分位数到均数与标准差的转换  【中国循证医学杂志, 17: 1350-1356, 2017】
    
    
    -- This paper establishes a new "rule of thumb" between the sample mean, median and mid-range. The paper has been recognized as a Highly Cited Paper (and a Hot Paper in 2019-2020) in ISI Web of Science, with a total of 1800 citations (and 2100+ citations in Google Scholar) as of August 2024.
    
    
    
33. Yan Zhou, Xiang Wan, Baoxue Zhang and Tiejun Tong (2018)
    Classifying next-generation sequencing data using a zero-inflated Poisson model
    Bioinformatics, 34: 1329-1335.   [R package for ZIPLDA]
    
    
34. Yuejin Zhou, Yebin Cheng, Wenlin Dai and Tiejun Tong (2018)
    Optimal difference-based estimation for partially linear models
    Computational Statistics, 33: 863-885.
    
    

2017


35. Wenlin Dai, Tiejun Tong and Lixing Zhu (2017)
    On the choice of difference sequence in a unified framework for variance estimation in nonparametric regression
    Statistical Science, 32: 455-468.
    
    
36. Zongliang Hu, Kai Dong, Wenlin Dai and Tiejun Tong (2017)
    A comparison of methods for estimating the determinant of high-dimensional covariance matrix
    International Journal of Biostatistics, 13: 20170013.
    
    
37. Yan Zhou, Baoxue Zhang, Gaorong Li, Tiejun Tong and Xiang Wan (2017)
    GD-RDA: A new regularized discriminant analysis for high dimensional data
    Journal of Computational Biology, 24: 1099-1111.
    
    
38. Yujie Li, Gaorong Li, Heng Lian and Tiejun Tong (2017)
    Profile forward regression screening for ultra-high dimensional semiparametric varying coefficient partially linear models
    Journal of Multivariate Analysis, 155: 133-150.
    
    

2016


39. Wenlin Dai, Tiejun Tong and Marc G. Genton (2016)
    Optimal estimation of derivatives in nonparametric regression
    Journal of Machine Learning Research, 17(164): 1-25.
    
    
40. Kai Dong, Hongyu Zhao, Tiejun Tong and Xiang Wan (2016)
    NBLDA: Negative binomial linear discriminant analysis for RNA-Seq data
    BMC Bioinformatics, 17: 369.
    
    
41. Jiacheng Yuan, Herbert Pang, Tiejun Tong, Dong Xia, Wenzhao Guo and Peter Mesenbrink (2016)
    Seamless phase IIa/IIb and enhanced dose finding adaptive design
    Journal of Biopharmaceutical Statistics, 26: 912-923.
    
    
42. Kai Dong, Herbert Pang, Tiejun Tong and Marc G. Genton (2016)
    Shrinkage-based diagonal Hotelling tests for high-dimensional small sample size data
    Journal of Multivariate Analysis, 143: 127-142.
    
    
43. Fengyang He, Yebin Cheng and Tiejun Tong (2016)
    Estimation of high conditional quantiles using the Hill estimator of the tail index
    Journal of Statistical Planning and Inference, 176: 64-77.
    
    

2015


44. Yebin Cheng, Dexiang Gao and Tiejun Tong (2015)
    Bias and variance reduction in estimating the proportion of true null hypotheses
    Biostatistics, 16: 189-204.   [R codes]
    
    
45. Yuejin Zhou, Yebin Cheng, Lie Wang and Tiejun Tong (2015)
    Optimal difference-based variance estimation in heteroscedastic nonparametric regression
    Statistica Sinica, 25: 1377-1397.
    
    
46. Cheng Wang, Guangming Pan, Tiejun Tong and Lixing Zhu (2015)
    Shrinkage estimation of large dimensional precision matrix using random matrix theory
    Statistica Sinica, 25: 993-1008.
    
    
47. Yiping Yang, Gaorong Li and Tiejun Tong (2015)
    Corrected empirical likelihood for a class of generalized linear measurement error models
    Science China Mathematics, 58: 1523-1536.
    
    
48. Wenlin Dai, Yanyuan Ma, Tiejun Tong and Lixing Zhu (2015)
    Difference-based variance estimation in nonparametric regression with repeated measurement data
    Journal of Statistical Planning and Inference, 163: 1-20.
    
    

2014


49. Xiang Wan, Wenqian Wang, Jiming Liu and Tiejun Tong (2014)
    Estimating the sample mean and standard deviation from the sample size, median, range and/or interquartile range
    BMC Medical Research Methodology, 14: 135.
    
         [Online Calculator]
    
    
    -- This paper establishes an improved "rule of thumb" between the sample range and the sample standard deviation. The paper has been recognized as a Highly Cited Paper (and a Hot Paper in 2016) in ISI Web of Science, with a total of 5700 citations (and 7400+ citations in Google Scholar) as of August 2024.
    
    
    
50. Gaorong Li, Heng Peng, Kai Dong and Tiejun Tong (2014)
    Simultaneous confidence bands and hypothesis testing for single-index models
    Statistica Sinica, 24: 937-955.
    
    
51. Cheng Wang, Tiejun Tong, Longbing Cao and Baiqi Miao (2014)
    Nonparametric shrinkage mean estimation for quadratic loss functions with unknown covariance matrices
    Journal of Multivariate Analysis, 125: 222-232.
    
    
52. Tiejun Tong, Cheng Wang and Yuedong Wang (2014)
    Estimation of variances and covariances for high-dimensional data: a selective review
    Wiley Interdisciplinary Reviews: Computational Statistics, 6: 255-264.
    
    

2013


53. Tiejun Tong, Yanyuan Ma and Yuedong Wang (2013)
    Optimal variance estimation without estimating the mean function
    Bernoulli, 19: 1839-1854.
    
    
54. Herbert Pang, Tiejun Tong and Michael K. Ng (2013)
    Block-diagonal discriminant analysis and its bias-corrected rules
    Statistical Applications in Genetics and Molecular Biology, 12: 347-359.
    
    
55. Gaorong Li, Heng Peng and Tiejun Tong (2013)
    Simultaneous confidence bands for nonparametric fixed effects panel data models
    Economics Letters, 119: 229-232.
    
    

2012


56. Tiejun Tong, Liang Chen and Hongyu Zhao (2012)
    Improved mean estimation and its application to diagonal discriminant analysis
    Bioinformatics, 28: 531-537.
    
    
57. Tiejun Tong, Homin Jang and Yuedong Wang (2012)
    James-Stein type estimators of variances
    Journal of Multivariate Analysis, 107: 232-243.
    
    
58. Herbert Pang, Stephen George, Ken Hui and Tiejun Tong (2012)
    Gene selection using iterative feature elimination random survival forests
    IEEE/ACM Transactions on Computational Biology and Bioinformatics, 9, 1422-1431.
    
    

2011


59. Liqian Peng and Tiejun Tong (2011)
    A note on two-sample t test with one variance unknown
    Statistical Methodology, 8: 528-534.
    
    

2010


60. Song Huang, Tiejun Tong and Hongyu Zhao (2010)
    Bias-corrected diagonal discriminant rules for high-dimensional classification
    Biometrics, 66: 1096-1106.
    
    
61. Nairanjana Dasgupta, Eleanne Solorzano and Tiejun Tong (2010)
    Comparing multiple treatments to both positive and negative controls
    Journal of Statistical Planning and Inference, 140: 180-188.
    
    

2009


62. Herbert Pang, Tiejun Tong and Hongyu Zhao (2009)
    Shrinkage-based diagonal discriminant analysis and its applications in high-dimensional data
    Biometrics, 65: 1021-1029.
    
    

2008


63. Tiejun Tong and Hongyu Zhao (2008)
    Practical guidelines for assessing power and false discovery rate for a fixed sample size in microarray experiments
    Statistics in Medicine, 27: 1960-1972.   [R codes]
    
    
64. Liang Chen, Tiejun Tong and Hongyu Zhao (2008)
    Considering dependence among genes and markers for false discovery control in eQTL mapping
    Bioinformatics, 24: 2015-2022.
    
    

2007


65. Tiejun Tong and Yuedong Wang (2007)
    Optimal shrinkage estimation of variances with applications to microarray data analysis
    Journal of the American Statistical Association, 102: 113-122.
    
    
66. Anna Liu, Tiejun Tong and Yuedong Wang (2007)
    Smoothing spline estimation of variance function
    Journal of Computational and Graphical Statistics, 16: 312-329.
    
    

2005


67. Tiejun Tong and Yuedong Wang (2005)
    Estimating residual variance in nonparametric regression using least squares
    Biometrika, 92: 821-830.
    
    

2004


68. Chun Su and Tiejun Tong (2004)
    Almost sure convergence of the general Jamison weighted B-valued random variables
    Acta Mathematica Sinica, English Series, 20: 181-192.
    
    

    Selected collaborative papers