硕士生导师

郭建华

建华,中共党员,教授,博士生导师,现任拼搏平台党委副书记,董事长。1999年博士毕业于北京大学,曾任东北师范大学党委常委,副董事长。国务院学位委员会学科评议组统计学科召集人,国家杰出青年科学基金获得者,教育部“长江学者奖励计划”特聘教授,“新世纪百千万人才工程”国家级人选,教育部新世纪优秀人才,国务院政府特殊津贴获得者,IMS会士,ISI选举会士;担任国家社会科学基金学科规划评议组成员,国家自然科学基金委员会数学学科会评专家;兼任中国现场统计研究会理事长,中国统计学会副会长;担任世界著名期刊《Journal of the American Statistical Association》编委、《Communications in Statistics》编委,《Frontiers in Genetics》副主编,印度统计期刊《Sankhya B: Applied and Interdisciplinary Statistics》联合主编(Co-Editor),国内核心期刊《应用数学学报》、《高校应用数学学报》、《应用概率统计》等编委,CSSCI期刊《统计研究》、《数理统计与管理》、《统计与信息论坛》编委。

主持包括科技部国家重点研发计划、国家自然科学基金杰出青年基金、国家自然科学基金重点项目、教育部“长江学者和创新团队发展计划”创新团队等在内基金项目20余项,其中含国家自然科学基金项目12项。目前已指导博士生近30人,博士后11人。主要从事大数据统计学、统计机器学习、因果推断和生物统计学的方法论研究及其在各行各业的实际应用工作。近年来在国内外著名期刊上共发表论文百余篇,更有不少发表在世界最顶尖的统计学、人工智能等期刊上。获得教育部科技进步奖二等奖2项、国家统计局科技进步一等奖1项。


主要学习和工作经历

【学习、访问经历】

1983.08-1986.07 宁阳师范学校(中专)学习

1986.09-1988.07 泰安师范专科学校(现为泰山学院),数学教育专业学习

1988.08-1990.07 曲阜师范大学数学与应用数学专业,获理学学士学位

1990.09-1993.07 北京大学概率论与数理统计专业,获理学硕士学位

1996.09-1999.07 北京老员工物医学统计专业,获理学博士学位

2001.12-2002.12 美国耶鲁大学医学院流行病学与公共卫生系博士后研究员

【工作经历】

1993.07-1996.09  曲阜师范大学数学与计算机科学系助教、讲师

1999.07-2023.06  东北师范大学工作,2001年晋升教授,2003年聘为博士生导师

2000.09-2004.01  东北师范大学数学系副系主任   

2004.01-2008.01  东北师范大学拼搏平台副经理

2008.01-2013.10  东北师范大学拼搏平台经理

2013.08-2014.05  东北师范大学人事处处长

2014.05-2023.06  东北师范大学副董事长 

2023.06-      拼搏平台党委副书记、董事长


科研项目

1.基于国家急诊CT影像数据库的多病种精准快速联合筛查的数学方法与系统,国家自然科学基金委员会 数学天元基金项目,2023.01.01-2024.12.31,200万元,联合主持人;

2.本科统招生生源质量研究分析——以东北师范大学为例, 2021年中国高校产学研创新基金”新一代信息技术创新项目(一般项目, 2021ITA05019), 2022.11.30-2023.11. 29,2万元,主持人;

3.面向海量多源遥感数据处理的关键数学问题及其产业应用,科技部国家重点研发计划变革性技术关键科学问题重点专项2020年度定向项目(2020YFA0714100),2020.12-2025.11,472万元,主持人;

4.贝叶斯网分解理论及其应用,国家自然科学基金天元基金项目,2018.01- 2018.12, 20万元,主持人;

5.大数据的统计学基础与分析方法--大数据的稳健统计分析,国家自然科学基金重大项目之重点项目子课题,2017.01- 2021.12,255万元,主持人;

6.基于结构的网络数据统计分析,国家自然科学基金重点项目,2017.1-2021.12,236万元,主持人;

7.2016统计学青年骨干教师培训班,国家自然科学基金专项基金项目,2016.6-2016.12,70万元,主持人;

8.数据驱动的应用统计方法研究,2010年度教育部“长江学者和创新团队发展计划”创新团队,2011.1-2013.12,300万元,主持人;

9.汉语文本数据挖掘示范,吉林省科技厅社会发展重点项目,2010.4-2012.12,20万元,主持人;

10.应用统计方法研究,国家杰出青年科学基金,2011.1-2014.12,140万元,主持人;

11.汉语文本数据挖掘的统计方法,国家自然科学基金专项基金项目,2010.1-2010.12,10万元,主持人;

12.基因定位的统计方法研究,国家自然科学基金面上项目,2009.1-2011.12,29万元,主持人;

13.汉语文本数据挖掘的统计方法,国家自然科学基金专项基金项目,2009.1-2009.12,10万元,主持人;

14.非结构化数据的数学建模与机器学习(基于视觉认知的非结构化信息处理理论及关键技术 之课题2),国家重点基础研究发展计划—973计划课题(2007CB311002)2007.7-2012.8,47万元,研究骨干;

15.生物医学中的统计方法研究,国家自然科学基金重点项目,2005.1-2008.12,100万元,子课题负责人;

16.新世纪优秀人才支持计划,国家教育部(NCET-04-0310),2005.1-2007.12,50万元,主持人;

17.信息通讯技术(ICT)产业评价与比较研究,国家科技部,2005.1-2006.4,10万元,主持人;

18.分子遗传数据的统计分析方法,国家自然科学基金面上项目,2004.1-2006.12,16万元,主持人;

19.遗传证据的因果分析,国家杰出青年科学基金(海外),2004.1-2006.12,40万元,联合主持人;

20.生物信息学的统计分析方法,教育部科学技术重点项目,2004.1-2006.12,10万元,主持人;

21.人类复杂疾病的基因定位,吉林省杰出青年科学研究计划,2003.6-2006.5,10万元,主持人;

22.DNA分子数据的统计学方法研究,教育部优秀青年教团队助计划项目,2004.1-2006.12,8万元,主持人;

23.流行病学研究中的混杂现象和因果推断,国家自然科学基金青年项目,2001.1-2003.12,7万元,主持人;

24.DNA序列的统计特性及其遗传结构分析,教育部科学技术重点项目,2001.1-2003.12,13万元,项目组成员;

25.图模型,小波和谱估计,国家自然科学基金面上项目,1996.1-1998.12,15万元,项目组成员;

26.不完全数据的统计分析方法,国家自然科学基金面上项目,1991.1-1993.12,6万元,项目组成员。


获奖情况

27.第七届“全国优秀科技工作者”入选者,2016

28.吉林省教学成果奖二等奖,2014

29.教育部长江学者特聘教授,2012

30.吉林省第三批高级专家,2011

31.国家级教学团队概率论与数理统计专业教学团队,2010

32.新世纪百千万人才工程国家级人选,2009

33.第九届吉林省青年科技奖,2007

34.教育部自然科学奖二等奖,2007

35.首届新世纪优秀人才支持计划入选者,2005

36.吉林省第八批有突出贡献的中青年专业技术人才,2005

37.长春青年五四奖章获得者,2005

38.吉林省第一批拔尖创新人才第三层次人选,2005

39.获国务院政府特殊津贴,2004

40.吉林省杰出青年科学研究计划资助学者,2003

41.北京大学优秀博士论文和北京市优秀博士论文,2001

42.国家统计局第四届全国统计科学科技进步奖一等奖,1998

43.国家教委科技进步奖二等奖,1997


研究兴趣

1.大数据统计建模

2.网络数据的统计分析

3.高维数据分析

4.机器学习与Bayes网络

5.文本数据挖掘的统计方法

6.遗传流行病学

7.生物信息学

8.观察研究中的因果推断和建模

9.生物医学统计

10.科技评价的统计方法研究


学术论文

1. Yuan, C.F., Gao, Z.G., He, X., Huang, W. and Guo*, J.H. Two-way dynamic factor models for high-dimensional matrix-valued time series. Accepted by Journal of the Royal Statistical Society, Serials B, 2023.

2. Wang, J.Z., Zhang, J.F., Liu, B.H., Zhu*, J. and Guo*, J.H. Fast network community detection with profile-pseudo likelihood methods.Journal of the American Statistical Association, 2023, 118(542): 1359-1372. https://doi.org/10.1080/01621459.2021.1996378

3. Fan, J., Guo, J.H. and Zheng, S.R. Estimating number of factors by adjusted eigenvalues threshoding. Journal of the American Statistical Association, 2022, 117(538): 852- 861.

4. Zheng, T.Q., Guo*, J.H. and Ma, Y.Y. A two-way additive model with unknown group specific interactions applied on gene expression data. Biometrical Journal, 2022, 64:1007-1022.

5. Zheng, S.R., He, X. and Guo, J.H. Hypothesis testing for block-structured correlation for high-dimensional variables. Statistica Sinica, 2022, 32(2): 719-735. doi:https://doi.org/10.5705/ ss.202019.0319.

6. An, B.G., Feng, G.Z. and Guo*, J.H.Interaction identification and clique screening for classification with ultra-high dimensional discrete features. Journal of Classification, 2022,  39:122–146.https://doi.org/10.1007/s00357-021-09399-0

7. Hu, Y.Y., Wang, J.H., He, X. and Guo, J.H. Bayesian joint-quantile regression. Computational Statistics,2021, 36:2033–2053. https://doi.org/10.1007/s00180-020-00998-w.

8. Gao, Z.G., Guo*, J.H. and Ma, Y. Y. A note on statistical analysis of factor models of high dimension. Science China Mathematics, 2021, 64: 1905–1916, https://doi.org/10.1007/s11425-019-1698-1

9. Wang, J.Z., Liu, B.H. and Guo*, J.H. Efficient split likelihood-based method for community detection of large-scale networks.Stat. 2021;10:e349. https://doi.org/10.1002/sta4.349 [IF=0.766, II旗舰刊]

10. Wang, J.Z., Guo*, J.H. and Liu*, B.H. A fast algorithm for integrative community detection of multi-layer networks. Stat. 2021;10:e348. https://doi.org/10.1002/sta4.348

11. Zhou, C., Wang*, X.F. and Guo*, J.H. Learning mixed latent tree models. Journal of Machine Learning Research, 2020,21:1-35.

12. Zheng, S.R., Lin, R.T., Guo, J.H. and Yin, G.S. Testing homogeneity of high-dimensional covariance matrices.Statistica Sinica, 2020, 30: 35-53.

13. Zheng, S.R., Cheng, G.H., Guo, J.H. and Zhu, H.T. Test for high dimensional correlation matrices. The Annals of Statistics, 2019, 47(5): 2887-2921.

14. Yuan, C.F., Zhu, W.S., He, X. and Guo*, J.H. A mixture factor model with applications to microarray data. Test, 2019,28(1):60-76. https://doi.org/10.1007/s11749-018-0585-3

15. Guan, G.Y., Shan, N. and Guo*, J.H. Feature screening for ultrahigh dimensional binary data. Statistics and Its Interface, 2018, 11: 41-50.

16. Cui, X., Guo, J.H. andYang G.R. On the identifiability and estimation of generalized linear models with parametric nonignorable missing data mechanism. Computational Statistics and Data Analysis, 2017, 107: 64–80.

17. Wang, X.F., Guo*, J.H., Hao, L.Z. and Zhang, N.L.Spectral methods for learning discrete latent tree models. Statistics and Its Interface, 2017, 10: 677-698.

18. Wang, B., Diao*, H.A., Guo*, J.H., Liu, X.Y. and Wu, Y.H. Adaptive variable selection for extended Nijboer–Zernike aberration retrieval via lasso. Optics Communications, 2017, 385: 78-86.

19. Du, N., Wang, X.F., Guo*, J.H.and Xu, M.D. Attraction propagation: a user-friendly interactive approach for polyp segmentation in colonoscopy images. PLoS ONE, 2016, 11(5): e0155371. doi:10.1371/journal.pone.0155371.

20.Guo, J.H., Hu, J.C., Jing, B.Y. and Zhang, Z. Spline-Lasso in high-dimensional linear regression. Journal of the American Statistical Association, 2016, 111(513): 288--297.

21.Li, S.T., Chen, J.H., Guo*, J.H., Jing, B.Y., Tsang, S.Y. and Xue, H. Likelihood ration test for multisample mixture models and its application to genetic imprinting. Journal of the American Statistical Association, 2015, 110(510): 867--877.  

22.Shan, N., Dong, X.G., Xu, P.F. and Guo, J.H.Sharp bounds on survivor average causal effects when the outcome is binary and truncated by death. ACM Transactions On Intelligent Systems and Technology, 2015, 7(2): Article 18, 11pages. DOI: http://dx.doi.org/10.1145/2700498  

23.Xu, P.F., Guo*, J.H. and Tang, M.L. A localized implementation of the iterative proportional scaling procedure for Gaussian graphical models. Journal of Computational and Graphical Statistics, 2015, 24(1): 205--229.

24.Feng, G.Z., Guo*, J.H.,Jing, B.Y. and Sun, T.L. Feature subset selection using naive Bayes for text classification.Pattern Recognition Letters, 2015, 65: 109--115.

25.An, B.G., Guo, J.H. and Liu, Y.F. Hypothesis testing for band size detection of high dimensional banded precision matrices. Biometrika, 2014, 101(2): 477-483.

26.Guan, G.Y., Guo, J.H. and Wang, H.S. Varying naive Bayes models with application to classification of Chinese text documents.Journal of Business & Economic Statistics, 2014, 32(3): 445--456.

27.Cai, S.F., Li, B.C. and Guo*, J.H. A simplification of computing Markov bases for graphical models whose underlying graphs are suspensions of graphs. Statistica Sinica, 2014, 24: 447--461.    

28.Jin, L.N., Zhu, W.S., Yu, Y.Q., Kou, C.G., Meng, X.F., Tao, Y.C. and Guo*, J.H. Nonparametric tests of associations with disease based on U-statistics. Annals of Human Genetics, 2014, 78: 141--153.

29. Tang, M.L., Wu, Q., Tian, G.L. and Guo, J.H. Two-sample non-randomized response techniques for sensitive questions.  Communications in Statistics – Theory and Methods, 2014, 43(2): 408—425.

30.Liu, B.H. and Guo*, J.H. Collapsibility of conditional graphical models. Scandinavian Journal of Statistics, 2013, 40(2): 191--203.

31. Tsang, S.Y. , Zhong, S., Mei, L.L., Chen, J.H., Ng, S.K., Pun, F. W., Zhao, C., Jing, B.Y., Chark, R., Guo, J.H. , Tan, Y., Li, L., Wang, C.,  Chew,  S. H., and Xue, H. Social cognitive role of schizophrenia candidate gene GABRB2. PLoS ONE, 2013, 8(4): e62322. doi:10.1371/journal.pone.0062322.

32.Xiao, J., Zhu, W.S. and Guo, J.H. Large-scale multiple testing in genome-wide association studies via region-specific hidden Markov models.  BMC Bioinformatics, 2013, 14: 282.  http://www.biomedcentral.com/1471-2105/14/282

33.An, B.G., Guo*, J.H. and Wang, H.S. Multivariate regression shrinkage and selection by canonical correlation analysis. Computational Statistics and Data Analysis, 2013, 62: 93--107.                                                      

34.An, B.G., Wang, H.S. and Guo, J.H. Testing the statistical significance of an ultra-high-dimensional naive Bayes classifier. Statistics and Its Interface, 2013, 6: 223—229.                                                                                                    

35.Wang, X.F. and Guo*, J.H. The tree structure of graphs for various graphical models. Statistics and Its Interface, 2013, 6: 151—164.  

36. Li, B.C., Cai, S.F. and Guo*, J.H. A computational algebraic geometry method for conditional independence inference.Frontiers of Mathematics in China, 2013, 8(3): 567–582.                                                                                                

37.Li, B.C. and Guo*, J.H. Decomposition of two classes of structural models.  Frontiers of Mathematics in China, 2013, 8(6): 1323--1349.

38.Qi, B., Huang, W., Zhu, B., Zhong, X.F., Guo, J.H., Zhao, N., Xu, C.M., Zhang, H.K., Pang, J.S., Han, F. P. and Liu, B. Global transgenerational gene expression dynamics in two newly synthesized allohexaploid wheat (Triticum aestivum) lines. BMC Biology, 2012, 10: 3. Website http://www.biomedcentral.com/1741-7007/10/3

39.Xu, P.F., Guo*, J.H. and Tang, M.L. An improved Hara-Takamura procedure by sharing  computations on junction tree in Gaussian graphical models. Statistics and Computing, 2012, 22: 1125–1133.   doi: 10.1007/s11222-011-9286-4

40.Meng, X.Y., Guo*, J.H. and Su, B.T. Incidence coloring  of pseudo-Halin graphs. Discrete Mathematics, 2012, 312: 3276–3282.

41.Pei, Y.B., Tang, M.L., Wong, W.K. and Guo, J.H. Confidence intervals for correlated proportion differences from paired data in a two-arm randomized clinical trial. Statistical Methods in Medical Research,2012, 21(2): 167–187.

42.Feng, G.Z., Guo*, J.H., Jing, B.Y. and Hao, L.Z. A Bayesian feature selection paradigm for text classification.  Information Processing & Management, 2012, 48: 283–302.

43.Li, B.C. and Guo*, J.H.A note on one-factor analysis. Statistics and Probability Letters, 2012, 82(11): 1949–1952.

44.Shan, N. and Guo*, J.H. Covariate selection for identifying the causal effects of stochastic interventions using causal networks. Journal of Statistical Planning and Inference, 2012, 142: 212—220.  

45.Zheng, S.R., Guo, J.H., Shi, N.Z. and Tian, G.L.  Likelihood-based approaches for multivariate linear models under inequality constraints for incomplete data.Journal of Statistical Planning and Inference, 2012, 142: 2926—2942.

46.Xu, P.F. and Guo*, J.H. A new algorithm for decomposition of graphical models. Acta Mathematicae Applicatae Sinica, English Series, 2012, 28(3): 571—582.

47.Wang, X.F., Guo*, J.H. and He, X. Finding the minimal set for collapsible graphical models. Proceedings of the American Mathematical Society, 2011, 139: 361-373.

48.Xu, P.F., Guo, J.H. and He, X. An improved iterative proportional scaling procedure for Gaussian graphical models. Journal of Computational and Graphical Statistics, 2011(June), 20(2): 417--431.

49.Xu, P.F., Guo*, J.H. and Tang, M.L. Structural learning of Bayesian networks by testing complete separators in prime blocks. Computational Statistics and Data Analysis, 2011, 55: 3135-3147.

50.Shan, N. and Guo*, J.H. Bounds on average controlled direct effects with an unobserved response variable. Journal of Systems Science and Complexity, 2011, 24: 1154--1164.

51.Liu, B.H., Guo*, J.H. and Jing, B.Y. A note on minimal d-separation trees for structural learning. Artificial Intelligence, 2010, 174: 442-448.

52.Jin, L.N., Zhu, W.S. and Guo*, J.H.Genome-wide association studies using haplotype clustering with a new haplotype similarity. Genetic Epidemiology, 2010, 34: 633-641.

53.Zhao, H.X., Ma, W.Q. and Guo*, J.H. The AU algorithm for estimating equations in the presence of missing data. Statistics and Probability Letters, 2010, 80:639-647.

54.Shan, N. and Guo*, J.H. Covariate selection for identifying the effects of a particular type of conditional plan using causal networks. Frontiers of Mathematics in China,2010,5(4): 687-700.

55.周影,韩国牛,史宁中,冯荣锦,郭建华*,约束下多子女家系数据重组率的最大似然估计,中国科学:数学,2010, 40(10): 971-984.Zhou Y., Han G.N., Shi N.Z., Fung W.K. and Guo J.H.  Maximum likelihood estimates of recombination fractions under restrictions for family data with multiple offspring (in Chinese). Scientia Sinica Mathemation, 2010, 40 (10): 971-984, doi: 10.1360?012007-482

56.Tan, J., Lu, J., Huang, W., Huang, H., Li, L., Kong, C., Guo*, J.H. and Huang*, B. Q. Genome-wide analysis of histone H3 Lysine9 modifications in human mesenchymal stem cell osteogenic differentiation. PLoS ONE, 2009, 4(8): e6792. doi:10.1371.

57.Zhu, W.S., Kuk, A.Y.C. and Guo*, J.H. Haplotype inference for population data with genotyping errors. Biometrical Journal, 2009, 51 (4): 644–658.

58. Meng, X.Y., Guo*, J.H., Li, R.S., Chen, T. and Su, B.T. The total chromatic number of Pseudo-Halin graphs with lower degree, Discrete Mathematics, 2009, 309:982-986.

59.朱文圣,郭建华*,基于单倍型的复杂疾病基因定位研究,数理统计与管理,2009,28(2):370-379.

60. 赵红,朱文圣,郭建华,对含未知基因型个体的家系进行单倍型推断的EM方法,应用概率统计,2009,25(4):365-374.      

61. Zhou, Y., Shi, N.Z., Fung, W.K.and Guo*, J. H.  Maximum likelihood estimates of two-locus recombination fractions under some natural inequality restrictions,BMC Genetics, 2008, Vol. 9, article 1.

62. Pei, Y. B., Tang, M. L.and Guo, J. H. Testing the equality of two proportions for combined unilateral and bilateral data. Communications in Statistics --Simulation and Computation, 2008, 37(8):1515-1529.

63. Wang, X.,  Pan, L.,  Feng, Y.,  Wang, Y., Han, Q., Han , L., Han, S, Guo, J. H., Huang, B. and Lu, J.  p300 plays a role in expression and cell cycle arrest, Oncogene, 2008, 27:1894–1904.

64. Tan, J., Huang, H., Huang, W., Li, L., Guo*, J. H., Huang, B.Q. and Lu*, J. The genomic landscapes of histone H3-Lys9 modifications of gene promoter regions and expression profiles in human bone marrow mesenchymal stem cells. Journal of Genetics and Genomics, 2008, 35: 585-593.

65. Wang, X.F. and Guo*, J.H.  Junction trees of general graphs, Frontiers of Mathematics in China,2008, 3(3), 399-413.

66. Shi, N.Z., Geng, Z., Guo, J.H. and Tao, J. A project of applied statistical methods inChina: review and outlook, Statistics and Its Interface, 2008, 1: 197-207.

67. Yin, X.L., Ma, W.Q., Tang, M.L.and Guo*, J.H.  Testing for homogeneity of gametic disequilibrium across strata, BMC Genetics, 2007, Vol. 8, article 85.

68. Zhu, W.S., Fung, W.K. and Guo*, J.H. Incorporating genotyping uncertainty in haplotype frequency estimation in pedigree studies. Human Heredity, 2007, 64: 172-181.

69. Yin, X.L., Ma, W.Q., Tang, M.L. and Guo*, J.H. A test of homogeneity of Hardy-Weinberg disequilibrium across strata, European Journal of Human Genetics, 2006, 14: 1223-1230.                                                                                      

70. Tang, M.-L., Ng, H.K., Guo, J.H., Chan, W. and Chan, P.-S. Exact Cochran-Armitage trend tests: comparisons under different models, Journal of Statistical Computation and Simulation, 2006, 76(10): 847-859.

71.朱文圣,郭建华*,病例-对照研究中基因型不确定时单倍型关联分析的似然方法,中国科学 A辑,2006, 36: 403-417.                                            

72. Zhu, W.S. and Guo*, J.H. A likelihood-based method for haplotype association studies of case-control data with genotyping uncertainty, Science inChinaSeries A, 2006, 49: 130-144.

73. Guo, W., Fung, W.K., Shi, N.Z. and Guo, J.H. On the formula for admixture linkage disequilibrium, Human Heredity, 2005, 60:177-180.

74.Zheng, S.R., Shi, N.Z., Guo, J.H. The Restricted EM Algorithm under Linear Inequalities in a Linear Model with Missing Data, Science in China Series A, 2005,48: 819-828.                                                                                

75.郑术蓉、史宁中、郭建华,具有缺失数据的线性模型的一般线性不等式约束EM算法,中国科学 A辑,2005,35卷, 231-240.                            

76. Zheng, S.R., Shi, N.Z. and Guo, J.H. The restricted EM algorithm under inequality restrictions on the parameters. Journal of Multivariate Analysis, 2005, 92: 53-76.

77.Shao, C., Hu, D.H., Yan, L.K., Su, Z.M., Wang, R.S., Zhu, W.S., Guo, J. H., Shi, N.Z., Sun, H., Li, Z.S. and Sun, C.C. Structure exploration and function prediction of SARS coronavirus E protein, Chemical Journal of Chinese Universities-Chinese, 2005, 26: 1512-1516.

78.Guo, J. H., Ma, Y. P., Shi, N.-Z. and Lau, T.S. Testing for homogeneity of relative difference under inverse sampling, Computational Statistics and Data Analysis, 2004, 44: 613-624.                                                                                

79. Guo, J. H., Geng, Z. and Shi, N.-Z. Consecutive collapsibility of logistic regression coefficients over an ordinal background, Journal of Statistical Planning and Inference, 2003, 115, 59-67.                                                                    

80.Geng, Z., Guo, J.H. and Fung, T.W.K.  Criteria for confounders in epidemiological studies.   Journal of the Royal Statistical Society, Serials B., 2002, 64, 3-15.

81. Ma, Y. P., Guo*, J. H., Shi, N.-Z. and Tang, M.-L.  On the use of historical control  information for  trend test in carcinogenesis, Biometrics, 2002, 58, 917-927.

82.Tao, J., Guo, J. H. and Shi, N.-Z. Stepwise confidence procedure under unknown variances for toxicological evaluation, Biometrical Journal, 2002, 44, 149-160.

83.Tao, J., Shi, N.-Z., Guo, J.H. and Gao, W. Stepwise confidence procedure for the identification of minimum effective dose with unknown variances, Statistics and Probability Letters,  2002, 57,121-131.

84.郭建华,病因推断与混杂现象,东北师范大学自然科学版,2002,34卷,概率论与数理统计特刊,25-41.

85. 史宁中,郑术蓉,郭建华,正态模型下的约束EM算法,东北师范大学自然科学版,2002,34卷,概率论与数理统计特刊,91-94.

86.Guo, J.H., Geng, Z. and Fung, T.W.K.  Consecutive collapsibility of odds ratios over an ordinal background variable.   Journal of Multivariate Analysis, 2001, 79, 89--98.  

87.Geng, Z., Guo, J.H., Lau, T.S. and Fung, T.W.K.  Confounding, homogeneity and collapsibility for causal effects in epidemiological studies. Statistica Sinica, 2001, 11, 63-75.  

88.郭建华, 耿直,史宁中,Yule测度的可压缩性研究,中国科学 A辑,2001,  31, 324-331.

89.Guo, J.H., Geng, Z. and Shi, N-Z. On collapsibility of Yule's measure, Science in China Series A, 2001, 44, 829-836.

90.郭建华,马文卿,辅助交互作用的有序可压缩性,应用概率统计,2001,17卷,39--43.

91.郭建华,马文卿,随机独立性与回归独立性,北京大学学报(自然科学版),2000, 36, 18-23.

92. Guo, J.H. and Geng, Z. Consecutive collapsibility of relative risks. 数学进展1999, 28(5), 49-50.

93.Guo, J.H., Chen, W.Y. and Ma, W.Q. Collapsibility of directed association measures in linear models.黑龙江大学自然科学学报, 1998, 15卷第3期, 10-14.

94.耿直,郭建华,李广伟,流行病学研究中的因果推断及混杂现象,中华流行病学杂志,1997, 18特辑1号, 617-618.

95. Guo, J.H. and Geng, Z. Collapsibility of logistic regression coefficients, Journal of the Royal Statistical Society, Serials B, 1995, 57, 263-267.

96.Geng, Z.,Asano,Ch., Ichimura, M., Kimura, H., Guo, J.H.and Gong, M. Knowledge reduction and integration in probabilistic expert systems. ItalyStatistics Review: Statistica Applicata, 1994, 6, 349-356.

97.郭建华,梁志武,优比的可压缩性,曲阜师范大学学报,1994,  20卷第4期, 15-18.

98. Zhu, W.S., Guo*, J.H. A likelihood-based method to study haplotype association for case-control data with genotyping uncertainty. Proceedings of the 8th China-Japan Symposium on Statistics, 2004, 412-415,Guilin,China.

99.郭建华,  阴小林, Yule测度的 齐一性检验 , 2000年中国博士 后学术大会论文集 : 数学 物理 与地质分册,2001,452--455,科学出版社:北京。

100. Guo, J. H. and Shi, N.-Z. Testing for homogeneity of the risk differences against order restrictions. Proceedings of the 7thJapan-China Symposium on Statistics, 2000, 379-382.

101. Geng, Z. and Guo, J.H. Confounder and confounding in observational studies. Proceedings of Joint Statistical Conference, 1998,Beijing, 12-15.

102. Geng, Z., Wan, K., Tao, F. and Guo, J.H. Decomposition of mixed graphical models with missing data (Invited Paper). Proceedings of Contemporary Multivariate Analysis and Its Application,1997, E.49-E.54.

103. Geng, Z., Li, G.W. and Guo, J.H. Causal effect and confounding. Contributed papers of the 6th China-Japan Symposium on Statistics, 1997,Xi'an, 56-59.

104. Guo, J.H. and Geng, Z. Collapsibility of likelihood ratio tests in mixed graphical Interaction models. Proceedings of the Asian Conference on Statistical Computing, 1993,  53-56.

105. Guo, J.H.,Asano,Ch., Sunada, Y. and Geng, Z.Background variables in data analysis and observation. Proceedings of the 61st Symposium of theJapanStatistical Society, 1993, 23-24.

106. Gong, M., Geng, Z. and Guo, J.H. Local probabilistic updating in causal networks. Proceedings of the 1stAsian Conference on Statistical Computing, 1993, 49-52.

107. Geng, Z., Guo, J.H. and Gong, M. Hypergraph representation of contingency tables with incomplete data. Proceedings of the Symposium on Applied Mathematics for Young Chinese Scholars, Ed. by Wu, F., 1992, 166-73.

108. 国务院学位委员会第六届学科评议组 编,一级学科博士、硕士学位基本要求(上册),郭建华 参与编写其中的两章:0701 数学一级学科博士、硕士学位基本要求(159--169)、0714统计学一级学科博士、硕士学位基本要求(259--265)。高等教育出版社,2014年1月,北京。

109. 国家自然科学基金委员会、中国科学院(郭建华 参与编写),未来10年中国学科发展战略:数学。科学出版社,2012年1月,北京。

110. 郭建华(编委会成员之一),《2012高中数学联赛备考手册(预赛试题集锦)》,中国数学会普及工作委员会 组编,各省市数学会 联合编写,华东师范大学出版社,221页,2012年1月出版。

111. 郭建华(编委会成员之一),《2011高中数学联赛备考手册(预赛试题集锦)》,中国数学会普及工作委员会 组编,各省市数学会 联合编写,华东师范大学出版社,2011年1月出版。

112. 郭建华(编委会成员之一),《2010高中数学联赛备考手册(预赛试题集锦)》,中国数学会普及工作委员会 组编,各省市数学会 联合编写,华东师范大学出版社,230页,2010年1月出版。

113. 郭建华(编委会成员之一),《2009高中数学联赛备考手册(预赛试题集锦)》,中国数学会普及工作委员会组编,各省市数学会联合编写,华东师范大学出版社,261页,2009年1月出版。

114. 郭建华、王蕾。发展博士研究生教育,造就具有创新性的高层次科研队伍—关于拼搏平台博士公司产品机制改革的思考,研究生教学研究,2006年第一期(总第六期),P4-7。

115. 郭建华。师德师风之我见,《百名博士生导师话师表》,P80-84,东北师范大学出版社。 转载于《东北师大校报》,2005年6月5日(总第1050期),第二版。

116. 郭建华、 赵宏亮。适应新形势,探索新途径—数学系硕士研究生课程改革新思路,研究生教学研究,2004年第一期(总第五期),P8-9。

117. 高惠璇,郭建华,张庆峰,张利华 编译:SAS系统与股票市场分析,北京大学概率统计系,  1998.