• 2025/5/25: 書籍「コピュラ理論の基礎」が発売！

• 2025/4/1：広島大学・情報科学部の教授に着任しました！

• 2025/3/29: 統計連合大会でプレナリーセッション(9/8月)を開催します！

講演者: Dr. Virginie Rondeau (INSERM U1219, ISPED, University of Bordeaux, France)、題目: Assessing surrogacy from joint modeling and mediation analysis when surrogates are either censored event times or longitudinal biomarker: cancer application、指定討論者: 大庭幸治(東大), 折原隼一郎(東医大), 曾議寬(台湾中央大)

• 2025/3/29, I will serve as Associate Editor, Communications in Statistics - Simulation and Computation (2025/4-)

• 2025/3/29, I will serve as Associate Editor, Communications in Statistics - Theory and Methods (2025/4-)

• 2025/2, ねこすたっと氏の記事に紹介されました：Joint Frailty-Copula Modelを使った生存時間解析：理論編、実践編

• Call for papers: Sequential Sampling Methods for Statistical Inference 

• I will serve as Associate Editor for Statistical Papers (2025-)

• I will a Co-Chair of EcoSta 2025 (@Waseda University, Tokyo, August 21-23, 2025)

 * is corresponding author

Journal Articles (100 articles) (Peer-reviewed)

1. Nakazono K, Uozumi R, Emura T* (2025) Parametric inference for the Mann-Whitney effect under survival copula models, Stat Pap, accepted

2. Teranishi R, Furukawa K, Emura T* (2025) A Two-Stage Estimation Approach to Cox Regression Under the Five-Parameter Spline Model, Mathematics 13(4): 616

3. Taketomi N, Shih JH, Emura T* (2025) Confidence interval for a univariate normal mean based on a pretest estimator, Advances in Shrinkage and Penalized Estimation Strategies, Honoring the Contributions of Professor A. K. Md. Ehsanes Saleh, Springer, accepted

4. Sun LH*, Wang YK,  Liu LH, Emura T, Chiu CY (2025) Change point estimation for Gaussian time series data with copula-based Markov chain models,  Comp Stat 40(3):1541–81

5. Kwon J, Emura T, Ha ID* (2025) Copula-based deep neural networks for clustered survival data, Comm Stat Appl Methods 32(3):389-400

6. Aizawa Y, Emura T, Michimae H* (2025) Bayesian ridge estimators based on copula-based joint prior distributions for logistic regression parameters, Comm Stat-Simul 54(1):252-266

7. Emura T*, Ditzhaus M, Dobler D, Murotani K (2024) Factorial survival analysis for treatment effects under dependent censoring, Stat Methods Med Res 33(1):61-79

8. Nakazono K, Lin YC, Liao GY, Uozumi R, Emura T* (2024) Computation of the Mann–Whitney effect under parametric survival copula models. Mathematics 12(10): 1453

9. Lo SM, Wilke RA*, Emura T (2024) A semiparametric model for the cause-specific hazard under risk proportionality Compt Stat Data Anal 195: 107953

10. Lin YH, Sun LH, Tseng YJ, Emura T* (2024) The Pareto type I joint frailty-copula model for clustered bivariate survival data, Comm Stat-Simul 53(4):2006–30

11. Huang XW, Emura T* (2024) Computational methods for a copula-based Markov chain model with a binomial time series, Comm Stat-Simul 53(4):1973-90

12. Emura T*, Matsumoto K, Uozumi R, Michimae H (2024) g.ridge: an R package for generalized ridge regression for sparse and high-dimensional linear models, Symmetry 16(2):223

13. Michimae H*, Emura T, Miyamoto A,  Kishi K (2024) Bayesian parametric estimation based on left-truncated competing risks data under bivariate Clayton copula models, J Appl Stat 51(13): 2690-708

14. Taketomi N, Konno Y, Chang YT, Mori M, Emura T* (2024) Confidence interval for normal means in meta-analysis based on a pretest estimator, Jpn J Stat Data Sci 7(2): 537–68

15. Michimae H*, Emura T, Furukawa K (2024) Bayesian ridge estimators based on a vine copula-based prior in Poisson and negative binomial regression models, J Stat Comput Sim 94(18): 3979-4000

16. Emura T*, Lai CC, Sun LH (2023) Change point estimation under a copula-based Markov chain model for binomial time series, Econ Stat 28 :120-37

17. Yeh CT, Liao GY, Emura T* (2023) Sensitivity analysis for survival prognostic prediction with gene selection: a copula method for dependent censoring, Biomedicines 11(3):797

18. Emura T*, Hsu WC, Chou WC (2023) A survival tree based on stabilized score tests for high-dimensional covariates, J Appl Stat 50(2):264-90

19. Shih JH, Konno Y, Chang YT, Emura T* (2023)  A class of general pretest estimators for the univariate normal mean, Commun Stat-Theor 25(8):2538-61

20. Michimae H*, Emura T (2023) Bayesian ridge regression for survival data based on a vine copula-based prior, AStA Adv Stat Anal 107: 755–84

21. Rehman H, Chandra N,* Emura T, Pandey M (2023) Estimation of the modified Weibull additive hazards regression model under competing risks, Symmetry 15(2):485

22. Shinohara S*, Lin YH, Michimae H, Emura T (2023) Dynamic lifetime prediction using a Weibull-based bivariate failure time model: a meta-analysis of individual-patient data, Comm Stat-Simul 52(2):349-68

23. Taketomi N, Emura T* (2023) Consistency of the estimator for the common mean in fixed-effect meta-analyses, Axioms 12(5):503

24. Emura T* , Michimae H (2022)  Left-truncated and right-censored field failure data: review of parametric analysis for reliability, Qual Reliab Eng Int 38:3919–34

25. Michimae H*, Emura T (2022) Bayesian ridge estimators based on copula-based joint prior distributions for regression coefficients, Comp Stat 37(5):2741–69

26. Emura T*, Michimae H, Matsui S (2022) Dynamic risk prediction via a joint frailty-copula model and IPD meta-analysis: building web applications. Entropy 24(5):589

27. Michimae H, Emura T* (2022) Likelihood inference for copula models based on left-truncated and competing risks data from field studies, Mathematics 10(13):2163

28. Shih JH, Konno Y, Chang YT, Emura T* (2022) Copula-based estimation methods for a common mean vector for bivariate meta-analyses, Symmetry 14(2):186

29. Kwon S, Ha ID*, Shih JH, Emura T (2022) Flexible parametric copula modelling approaches for clustered survival data, Pharm Stat 21(1): 69-88

30. Taketomi N, Yamamoto K, Chesneau C, Emura T* (2022) Parametric distributions for survival and reliability analyses, a review and historical sketch. Mathematics 10(20):3907

31. Taketomi N, Michimae H, Chang YT,  Emura T* (2022) meta.shrinkage: an R package for meta-analyses for simultaneously estimating individual means. Algorithms 15, 26.

32. Emura T*, Sofeu C, Rondeau V (2021) Conditional copula models for correlated survival endpoints: individual patient data meta-analysis of randomized controlled trials, Stat Methods Med Res 30(12):2634-50

33. Wang YC, Emura T*(2021)  Multivariate failure time distributions derived from shared frailty and copulas,  Jpn J Stat Data Sci 4(2):1105-31

34. Lin WC, Emura T, Sun LH* (2021) Estimation under copula-based Markov normal mixture models for serially correlated data, Comm Stat-Simul 50(12):4483-515

35. Huang X, Wang W, Emura T* (2021) A copula-based Markov chain model for serially dependent event times with a dependent terminal event, Jpn J Stat Data Sci 4(2):917-51

36. Shih JH, Emura T* (2021) On the copula correlation ratio and its generalization, J Multivar Anal 182: 104708

37. Shih JH, Lin TY, Jimichi M, Emura T* (2021) Robust ridge M-estimators with pretest and Stein-rule shrinkage for an intercept term, Jpn J Stat Data Sci 4(1): 107-50

38. Shih JH, Emura T* (2021) Penalized Cox regression with a five-parameter spline model, Commun Stat-Theor 50(16):3749–68

39. Sofeu C*, Emura T, Rondeau V (2021) A joint frailty-copula model for meta-analytic validation of failure time surrogate endpoints in clinical trials, Biometrical J 63(2): 423-46 

40. Dörre  A, Huang CY, Tseng YK, Emura T* (2021) Likelihood-based analysis of doubly-truncated data under the location-scale and AFT model, Comp Stat 36(1):375-408

41. Huang X, Emura T*(2021) Model diagnostic procedures for copula-based Markov chain models for statistical process control, Comm Stat-Simul 50(8): 2345-67

42. Taketomi N, Konno Y, Chang YT, Emura T* (2021) A meta-analysis for simultaneously estimating individual means with shrinkage, isotonic regression and pretests, Axioms 10(4): 267

43. Emura T*, Shih JH, Ha ID, Wilke RA (2020) Comparison of the marginal hazard model and the sub-distribution hazard model for competing risks under an assumed copula, Stat Methods Med Res 29(8): 2307–27

44. Sun LH*, Lee CS, Emura T (2020) A Bayesian inference for time series via copula-based Markov chain models, Comm Stat-Simul 49(20): 2897-913

45. Wu BH, Michimae H, Emura T* (2020) Meta-analysis of individual patient data with semi-competing risks under the Weibull joint frailty-copula model. Comp Stat 35(4):1525-52

46. Emura T*, Hsu JH (2020) Estimation of the Mann-Whitney effect in the two-sample problem under dependent censoring Compt Stat Data Anal 150: 106990

47. Wang YC, Emura T*, Fan TH, Lo SM, Wilke RA (2020) Likelihood-based inference for a frailty-copula model based on competing risks failure time data, Qual Reliab Eng Int 36(5):1622-38

48. Emura T* and Pan CH (2020) Parametric maximum likelihood inference and goodness-of-fit tests for dependently left-truncated data, a copula-based approach, Stat Pap 61:479-501

49. Michimae H*, Matsunami M, Emura T (2020) Robust ridge regression for estimating the effects of correlated gene expressions on phenotypic traits, Environ Ecol Stat 27: 41-72

50. Emura T*, Matsui S, Chen HY (2019) compound.Cox: univariate feature selection and compound covariate for predicting survival, Comput Methods Programs Biomed 168: 21-37

51. Shih JH, Emura T*(2019) Bivariate dependence measures and bivariate competing risks models under the generalized FGM copula, Stat Pap 60(4): 1101-18

52. Ha ID*, Kim JM, Emura T (2019) Profile likelihood approaches for semiparametric copula and frailty models for clustered survival data, J Appl Stat 46: 2553-71

53. Sofeu C, Emura T, Rondeau V* (2019) One-step validation method for surrogate endpoints in multiple RCTs with failure-time endpoints, Stat Med 38: 2928-42

54. Shih JH, Chang YT, Konno Y, Emura T* (2019) Estimation of a common mean vector in bivariate meta-analysis under the FGM copula, Statistics 53(3): 673-95.

55. Shih JH, Lee W, Sun LH, Emura T* (2019) Fitting competing risks data to bivariate Pareto models, Commun Stat-Theor 48(5): 1193-220

56. He Z, Emura T* (2019) Likelihood inference under the COM-Poisson cure model for survival data - computational aspects, J Chinese Stat Assoc 57: 1-42

57. Emura T*, Nakatochi M, Matsui S, Michimae H, Rondeau V (2018) Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: meta-analysis with a joint model, Stat Methods Med Res 27(9): 2842-58

58. Emura T*, Liao YT (2018) Critical review and comparison of continuity correction methods: The normal approximation to the binomial distribution. Commun Stat-Simul 47(8), 2266-85

59. Shih JH, Emura T*(2018) Likelihood-based inference for bivariate latent failure time models with competing risks under the generalized FGM copula, Comp Stat 33(3): 1293-323

60. Michimae H*, Yoshida A, Emura T , Matsunami M, Nishimura K (2018) Reconsidering the estimation of costs of phenotypic plasticity using the robust ridge estimator, Ecol Inform 44: 7-20

61. Emura T*, Nakatochi M, Murotani K, Rondeau V (2017) A joint frailty-copula model between tumour progression and death for meta-analysis, Stat Methods Med Res 26(6): 2649-66

62. Yang SP, Emura T*, (2017) A Bayesian approach with generalized ridge estimation for high-dimensional regression and testing, Commun Stat-Simul 46(8): 6083-105

63. Emura T*, Hu YH, Konno Y (2017) Asymptotic inference for maximum likelihood estimators under the special exponential family with double-truncation, Stat Pap 58(3): 877-909

64. Emura T*, Long TH, Sun LH (2017) R routines for performing estimation and statistical process control under copula-based time series models, Commun Stat-Simul 46: 3067-87

65. Chen AC, Emura T*(2017) A modified Liu-type estimator with an intercept term under mixture experiments, Commun Stat-Theor 46(13): 6645-67

66. Emura T*, Michimae H (2017) A copula-based inference to piecewise exponential models under dependent censoring, with application to time to metamorphosis of salamander larvae, Environ Ecol Stat 24(1): 151–73

67. Emura T, Chen YH* (2016) Gene selection for survival data under dependent censoring, a copula-based approach, Stat Methods Med Res 25(6): 2840–57

68. Emura T*, Wang W (2016) Semiparametric inference for an accelerated failure time model with dependent truncation, Ann Inst Stat Math 68 (5): 1073–94

69. Emura T*, Shiu-SK (2016) Estimation and model selection for left-truncated and right-censored lifetime data with application to electric power transformers analysis, Commun Stat-Simul 45(9): 3171–89

70. Emura T*, Ho YT (2016) A decision theoretic approach to change point estimation for binomial CUSUM control charts, Sequential Anal 35(2): 238-53

71. Hsu TM, Emura T, Fan TH* (2016) Reliability inference for a copula-based series system life test under multiple type-I censoring, IEEE T Reliab 65(2): 1069-80

72. Hu YH, Emura T* (2015) Maximum likelihood estimation for a special exponential family under random double-truncation, Comp Stat 30(4): 1199-229

73. Emura T*, Murotani K (2015) An algorithm for estimating survival under a copula-based dependent truncation model, TEST 24 (4): 734-51

74. Michimae H, Tezuka A, Emura T, Kishida O (2015) Environment-dependent trade-offs and phenotypuc plasticity in metamorphic timing, Evol Ecol Res 16:617-29

75. Emura T*, Konno Y, Michimae H (2015) Statistical inference based on the nonparametric maximum likelihood estimator under double-truncation, Lifetime Data Anal 21(3): 397-418

76. Emura T*, Lin YS (2015) A comparison of normal approximation rules for attribute control charts, Qual Reliab Eng Int 31(3): 411–18

77. Emura T*, Konno Y (2014) Erratum to: Multivariate normal distribution approaches for dependently truncated data, Stat Pap 55 (4): 1233-36

78. Long TH, Emura T* (2014) A control chart using copula-based Markov chain models, J Chinese Stat Assoc 52(4): 466-96

79. Emura T*, Kao FH, Michimae H (2014) An improved nonparametric estimator of sub-distribution function for bivariate competing risk models, J Multivar Anal 132: 229-41

80. Emura T, Chen YH*, Chen HY (2012) Survival prediction based on compound covariate method under Cox proportional hazard models PLoS ONE 7(10) doi:10.1371/journal.pone.0047627

81. Emura T, Wang W* (2012) Nonparametric maximum likelihood estimation for dependent truncation data based on copulas, J Multivar Anal 110: 171-88

82. Michimae H*, Emura T (2012) Correlated evolution of phenotypic plasticity in metamorphic timing, J Evolution Biol 25: 1331-39

83. Emura T, Konno Y* (2012) A goodness-of-fit tests for parametric models based on dependently truncated data, Compt Stat Data Anal 56: 2237-50

84. Emura T, Konno Y* (2012) Multivariate normal distribution approaches for dependently truncated data, Stat Pap 53(1): 133-49

85. Emura T, Wang W*, Hung HN (2011) Semi-parametric inference for copula models for dependently truncated data, Stat Sinica 21: 349-67

86. Wang W*, Emura T (2011) Comments on inference in multivariate Archimedean copula models by Genest et al., TEST 20: 276-80

87. Emura T, Lin CW, Wang W* (2010) A goodness-of-fit test for Archimedean copula models in the presence of right censoring, Compt Stat Data Anal 54: 3033-43

88. Emura T, Wang H* (2010) Approximate tolerance limits under the log-location-scale models in the presence of censoring, Technometrics 52(3): 313-23

89. Emura T, Wang W* (2010) Testing quasi-independence for truncation data, J Multivar Anal 101: 223-39

In Press (2025-)

90. Ali A, Pathak AK, Arshad M, Emura T (2024+) Copula-based regression estimation in the presence of outliers, Comm Stat-Simul, 10.1080/03610918.2024.2372657

日本語論文（査読あり）:

91. 武冨奈菜美*, 渡辺元宗, 今野良彦, 森美穂子, 江村剛志  (2025) メタ分析のためのデータを用いた個々の研究の正規母平均のPretest推定量, 日本統計学会誌, 第54 巻2号:73-108

92. 江村剛志*, 室谷健太 (2025) 従属打ち切りの下での治療効果推定のための要因計画・要因分析－コピュラに基づく 方法－, 統計数理 第73巻2号:xxx 

93. 中薗孝輔*, 魚住龍史, 江村剛志 (2025予定) パラメトリックコピュラモデルを用いた相関のある生存時間データにおけるMann-Whitney 効果の感度分析, 日本統計学会誌 (印刷中)

94. 寺西 蓮, 古川 恭治, 江村剛志* (2025予定) 比例ハザードモデルにおける回帰係数とベースラインハザード関数の推定法- Cox回帰法, ワイブル回帰法, ポアソン回帰法, スプライン回帰法の比較 -, 日本統計学会誌 (印刷中)

95. 江村剛志 古川恭治* (2024) フレイルティモデル -生存分析におけるハザードのランダム効果-, 計量生物学, 第45巻2号:215-245

96. 江村剛志 大庭幸治* (2024) 生存時間変数に対する代替性評価 –メタアナリシスアプローチ–, 計量生物学, 第45巻1号:67–85

97. 江村剛志* (2023)  安定化スコア検定を用いた高次元生存データに基づく決定木の構築法, 日本統計学会誌 第52巻;第2号:373-390

98. 江村剛志* (2023) 生存時間の２標本問題 - コピュラに基づく従属打ち切り問題への対処 -, 日本統計学会誌 第52巻;第2号:295-317

99. 江村剛志* (2021) コピュラ・マルコフ連鎖モデルによる定常時系列解析 ―パラメトリック推定と統計的工程管理―, 日本統計学会誌 第51巻;第1号:41-73

100. 江村剛志*, 道前洋史 (2020) コピュラを用いた生存時間解析 -相関のあるエンドポイントとメタ分析の活用-. 統計数理 第68巻;第1号:147–174

日本語予稿など（査読なし）:

• 江村剛志*, 道前洋史(2024), パラメトリック潜在故障時間コピュラモデルに基づく左側切断・競合リスクデータによるベイズ推定, 2024年度応用統計学会年会

• 江村剛志*, 松本晃太郎, 魚住龍史, 道前洋史 (2024) 高次元・スパースな線形モデルにおける一般化リッジ回帰と R パッケージ「g.ridge」2024年度日本計量生物学会年会, 予稿集

• 武冨奈菜美, 張元宗, 今野良彦, 森美穂子, 江村剛志(2023) メタ分析における正規母平均の Pretest 推定量に基づくPivot信頼区間, 研究集会「データサイエンスにおける統計的理論・方法論の新展開」九州大学 伊都キャンパス, 予稿集

• 岡田茜*, 江村剛志 (2023) 凹凸関数から考えるイベントヒストリー解析,  信学技報, R2023-37, 1-5

• 江村剛志*, 道前洋史 (2023) 左切断された競合リスクのコピュラモデル～ 尤度に基づくフィールド寿命データの解析 ～, 信学技報, R2023-39, 12-15

• 道前洋史, 江村剛志* (2022) ヴァインコピュラで事前分布をモデリングしたベイズリッジ推定量,  信学技報, R2022-38, 37-42

• 王尹辰, 江村剛志* (2021) コピュラとフレイルティ混合効果から導かれる多変量故障時間分布, 日本統計研究所所報, 54(統計的モデリング), 18-39

• 江村剛志*, 道前洋史 (2021) 左切断・右打ち切りのあるフィールド寿命データ解析 －パラメトリックモデルに基づく統計的推論と信頼性の予測－, 信学技報, vol. 121, no. 216, R2021-31, 7-12

Conference Proceedings (not Peer reviewed)

• Emura T* (2019/12/7-8), Comparing the marginal hazard model and the sub-distribution hazard model under an assumed copula, in a Statistics session chaired by Prof Tsung-Jen Shen (沈宗荏); 2019 TMS Meeting (數學年會), Chung Hsing Univ, Taiwan

• Emura T*, Shih JH (2019/6/3-7) Programs for semiparametric Cox regression with cubic M-spline, 11th International Conference on MMR2019 Conference Proceedings, Hong Kong

• Wang YC, Emura T* (2019/6/3-7) A frailty-copula model for dependent competing risks in reliability theory, 11th International Conference on MMR2019 Conference Proceedings, Hong Kong 

• 江村剛志*, 松井茂之, Chen HY (2018/9/9-13) 単変量 Cox 回帰にもとづく遺伝子選択と複合共変量による生存期間の予測, 2018年度 統計関連学会連合大会, 東京 (in Japanese)

• Shih JH*, Chang YT, Konno Y, Emura T (2018/9/9-13) Maximum likelihood estimation of a common mean vector in the bivariate FGM copula model for meta-analysis, 2018 JJSM (Japanese Joint Statistical Meeting), Tokyo

Others (not Peer reviewed):

• 江村剛志, (translated by 施嘉翰) (2018),  研究成果報告：死亡時間之個人化預測,  自然科學簡訊第三十卷(第一期) (in Chinese)

• Emura T, Wang J, Katsuyama H (2008) Assessing the Assumption of the Strongly Ignorable Treatment Assignment Under Assumed Causal Models. Technical Reports of Mathematical Sciences, Chiba Univ 24(No. 8).

• Emura T, Wang W (2008), Asymptotic Analysis and Variance Estimation for Testing Quasi-independence under Truncation, Technical Reports of Mathematical Sciences, Chiba Univ  24 (No 12).

• Emura T, Konno Y (2009), Multivariate Parametric Approaches for Dependently Left-truncated Data Technical Reports of Mathematical Sciences, Chiba Univ  25 (No. 2).

• Emura T, Katsuyama H, Wang J (2013) Assessing the Treatment Eect on the Causal Models viaParametric Approaches with Applications to the Study of English EducationalEffect in Japan MPRA Paper No. 43996.

International conference:

• (2025) Inferring median survival under dependent censoring, Symposium in Honour of Marc Ditzhaus, Dortmund, Germany (2025/7/8)

• (2025) Parametric inference for the Mann-Whitney effect under survival copula models, Hitotsubashi Workshop on Dependence Modeling with Applications, Tokyo, Japan (2025/5/8)

• (2025) Parametric inference for the Mann-Whitney effect under survival copula models, ISI-ISM-ISSAS 2025 Joint Conference, The Institute of Statistical Mathematics, Tokyo, Japan (5-7, March, 2025)

• (2024) Estimation for the Mann-Whitney effect under parametric survival copula models, Organized (invited) session, CM Statistics 2024,  King's College London, UK (14-16 December 2024) 

• (2024) Survival Prognostic Analysis with Copula-Graphic Estimator for Dependent Censoring, ICSDS2024, National Chengchi University, Taipei, Taiwan

• (2023) Bayesian ridge regression for survival data based on a vine copula based prior, Organized (invited) session, Dec 16-18, CM Statistics 2023, Berlin, Germany: Session: Advancements of survival and duration models on 12/17 organized by Ralf Wilke

• (2023) Bayesian ridge regression for survival data based on a vine copula based prior, Organized (invited) session, Aug 1-3, EcoSta 2023, Tokyo, Japan 

• (2023)  A survival tree based on stabilized score tests for high-dimensional covariates, KSS-CSA-JSS invited session, June 29-July 1, The Korean Statistical Society Meeting 2023, Busan, Korea

• (2022)  Factorial survival analysis for treatment effects under dependent censoring, Dec 17-19, Organized (invited) session, CMStatistics 2022, London, UK

• (2022) Conditional copula models for correlated survival endpoints in individual patient data meta-analysis, June 4-6, Organized (Invited) session, EcoSta2022, Ryukoku Univ, Japan

• (2021) Change point estimation under a copula-based Markov chain model for binomial time series, International Symposium on Advanced Science and Technology (ISAST), NCHU, Taiwan

• (2019) Kendalls tau for survival endpoints in meta-analysis: A general definition and a conditional copula approach, Dec 16-18, Organized (invited) session, CMStatistics 2019, London, UK

• (2019) Compound Cox: univariate feature selection and compound covariates for predicting survival, June 27-28, Invited speaker, 3rd Pacific Rim Cancer Biostatistics Conference, Oregon, USA

• (2019) A clinician's guide for dynamic risk prediction of death using an R package joint.Cox, June 23-26, Invited session, WNAR/IMS Annual Meeting, Oregon, USA

• (2019) A frailty-copula model for dependent competing risks in reliability theory, June 3-7, Invited session, MMR 2019, Hong Kong

• (2019) Programs for semiparametric Cox regression with cubic M-spline, June 3-7, Invited session, MMR 2019, Hong Kong

• (2018) Comparison between the marginal hazard models and sub-distribution hazard models with an assumed copula, Dec 14-16, Organized (invited) session, CMStatistics 2018, Pisa, Italy.

• (2017) Dynamic prediction for time-to-death under the joint frailty-copula model, Dec 16-18, Organized (invited) session, CMStatistics 2017, London, UK.

• (2017) Personalized prediction of overall survival utilizing gene expressions Oct 12-13, Invited speech at 2nd Pacific Rim Cancer Biostatistics Workshop, Kanazawa, JAPAN

• (2017) Dynamic prediction involving high-dimensional factors based on the joint frailty-copula model, Invited session, ICSA Applied Statistics Symposium, June 25-28, Chicago, USA.

• (2016) Dynamic prediction according to tumour progression and genetic factors: Meta-analysis with a joint frailty-copula model, Dec 9-11, Organized (invited) session at CM Statistics 2016, Seville, Spain.

• (2015) Parametric maximum likelihood inference for copula models with dependently left-truncated data, Dec 12-14, Organized (invited) session at CM Statistics 2015, London, UK.

• (2014) Gene selection for survival data under dependent censoring, a copula-based approach, June 30-July 3, Invited session at IMS-APRM 2014, Taipei, TAIWAN

• (2014) Algorithms for estimating survival function under dependent left-truncation with applications to elderly residents’ lifetime analysis, Feb 20-21, invited talk for the conference supported by Grant-in-Aid for Scientific Research, at Shobi University, Kawagoe, JAPAN

• (2013) Statistical inference based on the NPMLE under double-truncation Dec 14-16, Organized (invited) session at CM Statistics 2013, London, UK.

• (2013) Gene selection for survival data under dependent censoring: a copula-based approach July 8-9, Poster at Workshop ATMS (Asymptotc Theory of Multidimensional Statistics), Rennes, FRANCE.  Picture

• (2012) Survival prediction based on compound covariate under Cox proportional hazard models Aug 26-31, IBC 2012, Kobe, JAPAN.

• (2011) Predicting survival outcomes based on compound covariate method under Cox proportional hazard models with microarrays Dec 16-19, 7th IASC-ARS Joint2011 Taipei Symposium, Academia Sinica, TAIWAN.

Seminar talks (International/English):

• (2025/7/1) Parametric inference for the Mann-Whitney effect under survival copula models, Seminar at Department of Mathematics, RWTH Aachen University, Germany

• (2025/6/5) A Generalized Ridge Regression Method for Sparse and High-Dimensional Linear Models, Invited Seminar at  Department of Statistics and Data Science, Pukyong National University, Korea

• (2025/5/28) A Generalized Ridge Regression Method for Sparse and High-Dimensional Linear Models, Invited Seminar at Institute of Statistical Science, Taipei, Taiwan

• (2024/12/11) Dependence modeling for bivariate survival data using the two-parameter BB1 copula, Mathematical Sciences, University of Plymouth, UK

• (2024/5/30) Introduction to copulas, Invited seminar talk, Department Spring Seminar 2024 (Statistics & Data Science,PKNU), South Korea

• (2024/5/30) Survival and decision tree - review and future work, Invited seminar talk, Department Spring Seminar 2024 (Statistics & Data Science,PKNU), Busan, South Korea

• (2024/3/20) Factorial survival analysis for treatment effects under dependent censoring, ISS, Academia Sinica, Taiwan

• (2023/12/29) Survival Prognostic Prediction with Gene Selection – Copula methods -, Invited seminar talk, Chang Gung University, Taiwan

• (2023/10/27) Overview of copulas and Bayesian ridge estimator, Invited seminar talk, MMSD, Osaka University, Japan

• (2023/7/3) Bayesian ridge estimator based on vine-copula priors, Invited seminar talk, Pukyong National University, Busan, South Korea

• (2018/7/6) A joint frailty-copula model for clustered semi-competing risks data, Invited seminar talk, Pukyong National University, Busan, South Korea

• (2016/11/11) Personalized dynamic prediction of death according to tumour progression and high-dimensional genetic factors: meta-analysis with a joint model, Biostatistics Workshop organized by Prof. Kenich Hayashi at Keio University, Kanagawa, Japan

• (2014/11/5) A joint frailty-copula model between clustered times to progression and deaths, Invited seminar talk at INSERM, Biostat, Bordeaux, FRANCE.

In Taiwan (conference, seminar):

• (2007/6/22-23) A Class of Log-rank Test for Quasi-independence of Truncation Variables, 第16屆南區統計研討會 (高雄大學)

• (2011/12/10) Nonparametric Maximum Likelihood Estimation for Dependent Truncation Data based on Copula  Annual Meeting of the Taiwan Math Soc (中原大學)

• (2010/7/6-7) A Goodness-of-fit Test for Archimedean Copula Models in the Presence of Right Censoring , 第19回南區統計研究會 (成大統計系)

• (2011/3/11) Copula modeling for dependent truncation data- Review and new development  TIMS Seminar (臺大數學科學中心)

• (2011/3/8) Copula modeling for dependent truncation Invited seminar talk at 中央大學、統計研究所

• (2011/5/9) Approximate tolerance limits under log-location-scale regression models in presence of censoring  Invited seminar talk at 中央研究院統計科學研究所

• (2011) Regression analysis for dependent truncation data, June 24-25, 第20回南區統計研究會, 中正大學國際會議廳

• (2012/3/28) A goodness-of-fit test based on the multiplier Bootstrap with application to left-truncated data, Invited seminar talk at 高雄大学統計所

• (2012/4/24) Copula-based inference for truncation models based on copulas, Invited seminar talk at 東海大学統計系

• (2012/12/13) Survival prediction using the Cox proportional hazard models with a high-dimensional covariates, Invited talk at 中興大學統計所

• (2013/4/22) Statistical inference based on  the nonparametric MLE under double-truncation, Invited seminar talk at 政治大學統計系

• (2013/5/17) An extension of the compound covariate prediction under the Cox proportional hazard models, Invited talk at 東華大學應用數學系

• (2013/6/28-29) Gene selection for survival data under dependent censoring: a copula-based approach, Invited talk at 第22屆南區統計研討會 (高大)

• (2014/10/15) An algorithm for Estimating Survival under a Copula-Based Dependent Truncation Model: with Applications to Elderly Human’s Surviva to be announced, Invited talk at 高雄大學統計所

• (2014/11/21) Semiparametric inference for an accelerated failure time model with dependent truncation, Invited talk at 清華大學統計所

• (2014/12/6) A joint frailty-copula model between disease progression and death for meta-analysis Special invited session at 台,日,韓 國際統計學術研討會 (交大).

• (2015/1/29) Univariate gene selection for survival data under dependent censoring: a copula-based approach, Invited talk at 國家衛生研究院

• (2015/6/27-28) A joint frailty-copula model for semicompeting risks data with meta-analysis, Contributed talk at 第24屆南區統計研討會 (彰師大)

• (2015/9/14) Semiparametric inference for an accelerated failure time model with dependent truncation, Invited talk at 中央研究院統計科學研究所

• (2015/11/5)  Asymptotic inference for maximum likelihood estimators under the special exponential family with double-truncation, Invited talk at 成功大學統計學系

• (2015/12/4) A joint frailty-copula model between tumour progression and death for meta-analysis, Invited session at 2015統計學術研討會(臺北大統計系)

• (2016/6/24-25) A copula-based dynamic prediction of death according to tumour progression and high-dimensional genetic factors: joint Cox proportional hazards models for meta-analytic data, Invited session, 第25屆南區統計研討會(中山大)

• (2017/6/23-24) Dynamic prediction involving high-dimensional genetic factors based on the joint frailty-copula model, Invited session at 第26屆南區統計研討會 (臺北大)

• (2017/12/8) Personalized prediction for time-to-death unde the joint frailty-copula model, Invited session at CSA-KSS-JSS 國際統計學術研討會 at (銘傳大)

• (2018/6/29-30) Parametric survival analysis with dependent truncation, a copula-based approach, Invited session, 第27屆南區統計研討會 (成大學統計系)

• (2018/11/9-10), Univariate feature selection and compound covariate for predicting survival, Invited session, 107年統計學術研討會 (中央統計所)

• (2019/3/8) Classification and prediction of survival with high-dimensional features, Invited seminar talk at 政治大學統計系

• (2019/6/21-22) CompoundCox: univariate feature selection and compound covariate for predicting survival, Invited session, 第28屆南區統計研討會 (中興大學)

• (2019/9/18) A copula-based Markov chain model for attribute data, Invited talk at Institute of Statistics, 高雄大學統計所

• (2019/12/7-8) Comparison of the marginal hazard model and the sub-distribution hazard model under an assumed copula, Invited talk at Invited session, 2019數學年會 (中興大學)

• (2020/8/20-21) The marginal hazard model and the sub-distribution hazard model for competing risks under an assumed copula. 第29屆南區統計研討會 (中正大學)

• (2020/8/20-21) Change point estimation based on copula-based Markov chain binomial time series model. 第29屆南區統計研討會 (中正大學)

• (2023/11/20) Overview of copulas and Bayesian ridge estimator, Invited talk at 中興大學統計所

• (2023/11/22) Factorial survival analysis for treatment effects under dependent censoring, Invited talk at 中興大學統計所

In Japan (in Japanese):

(2024/11/6), ロバストな2 パラメーターBB1コピュラモデルに関する2変量生存時間解析とコピュラモデル選択, 統計数理セミナー, 統計数理研究所

(2024/10/17), 従属打ち切りの下での治療（処理）効果推定のための要因分析 ～ コピュラによる方法 ～, 電子情報通信学会 信頼性研究会, 市民会館シアーズホーム（熊本市民会館）

(2024/9/27), 生存時間解析における代替性, 第22回バイオ統計学フォーラム, 久留米大学医学部

(2024/9/6), 二変量生存データ解析のためのロバストな 2 パラメーターBB1コピュラモデル, 2024年度統計関連学会連合大会, 医学統計(3)セッション

(2024/8/5), 論文紹介（Zhang & Jeong 2021）：クラスターランダム化試験によるセミ競合リスク下でのWin Ratio推定, 東北大病院

(2024/5/11) 高次元・スパースな線形モデルにおける一般化リッジ回帰とR パッケージ「g.ridge」, 九大医学部, 2024年度日本計量生物学会年会

(2024/5/9) パラメトリック潜在故障時間モデルに基づく左側切断・競合リスクデータによるベイズ推定, 九大医学部, 2024年度応用統計学会年会

(2024/1/26) コピュラ・グラフィック推定量―理論と応用―, 2023年度科学研究費シンポジウム, 東北大・情報科学研究科

(2023/12/6) コピュラの概要とベイズリッジ回帰, 2023年度統計数理セミナー, 統計数理研究所

(2023/11/13) メタ分析における正規母平均の Pretest 推定量に基づくPivot信頼区間, 研究集会「データサイエンスにおける統計的理論・方法論の新展開」九州大学 伊都キャンパス

(2023/9/28) 左切断された競合リスクのコピュラモデル ～ 尤度に基づくフィールドデータの解析 ～, 信頼性研究会, 久留米大学医学部

(2023/9/16) 生存時間解析における実験計画法と従属打ち切り問題,  接合関数（コピュラ）理論の新展開, 統計数理研究所

(2022/12/8) セミ競合リスク・相関のあるエンドポイントへのアプローチ, 2022年度計量生物セミナー「生存時間解析」, 中央大学

(2022/12/8) 周辺モデル・Frailty・コピュラ, 2022年度計量生物セミナー「生存時間解析」, 中央大学

(2022/10/7) ヴァインコピュラで事前分布をモデリングしたベイズリッジ推定量, 電子情報通信学会 信頼性研究会, 久留米大, 福岡サテライト

(2022/9/16) 生存時間に基づく要因実験計画法 —コピュラに基づく従属打ち切り問題への対処ー, 共同研究集会2022：接合関数（コピュラ）理論の新展開, 統計数理研究所

(2022/9/9) 正規分布の母平均のPretest推定量の累積分布関数とWald信頼区間, 法政大・日本統計研究所研究集会~統計的モデリングとその周辺~

(2022/9/6) 生存時間の２標本問題 - コピュラに基づく従属打ち切り問題への対処 -, 2022年度統計関連学会連合大会, 企画セッション「生存時間解析・イベントヒストリー分析」

(2022/3/30) 2 群間の生存時間の差の推定 —コピュラに基づく従属打ち切 り問題への対処—, 2022年度日本数学会年会, 特別講演

(2022/2/9) 安定化スコア検定を用いた生存データに基づく決定木の構築, 第6回 統計・機械学習若手シンポジウム

(2022/1/22)  本講演「jointモデル」の概要紹介, 統数研・医療健康データ科学研究センター, 国際シンポジウム

(2021/12/3) 高次元スコア検定を用いた生存データに基づく決定木の構築,  科研費シンポジウム「データサイエンス・統計学における方法論と応用の新展開」長崎大・情報データ科学部 植木研究室

(2021/10/22) 左切断・右打ち切りのあるフィールド寿命データ解析 ～ パラメトリックモデルに基づく統計的推論と信頼性の予測 ～, 電子情報通信学会 信頼性研究会

(2021/9/5-9) コピュラとフレイルティから導かれる多変量生存時間分布族. 2021年度統計関連学会連合大会, セッション「コピュラ研究の展開」, 長崎大学

(2021/8/12) コピュラと混合効果から導かれる多変量終了時間分布, 第1回 日本統計研究所 研究集会「統計的モデリングと統計的推測理論」法政大学

(2021/4/15) 複数の生存エンドポイントの同時解析ーフレイルティ・コピュラモデリングー, バイオ統計センター公開セミナー, 久留米大学バイオ統計センター

(2019/12/21) 患者の予後予測のためのウェブ・アプリケーションをＲパッケージjoint.CoxとShinyで開発,  2019年度 「データ解析環境Rの整備と利用」統計数理研究所 

(2018/12/8) compound.Cox: 単変量Cox回帰法にもとづく特徴選択（feature selection）のRパッケージ, 2018年度 「データ解析環境Rの整備と利用」統計数理研究所 

(2018/9/9-13) 単変量Cox回帰にもとづく遺伝子選択と複合共変量による生存期間の予測, 統計関連合大会 , 中央大学

(2017/3/27-28) 遺伝子発現量をCox回帰モデルに取り入れた生存期間の個別化予測, 科研費（基盤S）シンポジウム, アクロス福岡

(2010/1/21) Testing Quasi-independence for Truncation Data. 久留米大学バイオ統計センター

(2009/10/1-3) Testing Quasi-independence for Truncation Data. 科学研究費Symposium, 日本女子大学

(2008/8/7-10) Multivariate Statistical Inference on Randomly Truncated Data, 統計関連合大会 統計関連合大会 , 慶応義塾大学

(2007/8/18-20) 切断データにおける時間の独立性仮設検定法 , August 18-20, 科学研究費  Symposium, 日本女子大学

(2007/8/6-9) Testing the Assumption of Strongly Ignorable Treatment Assignment. 統計関連合大会 , 神戸大学

Supervised Ph.D

• Jia-Han Shih 施嘉翰(2020) Copula-based statistical inferences for a common mean vector and correlation ratios using bivariate data

Supervised Master 

• Wei-Chern Hsu 徐瑋辰 (2020) A survival tree based on stabilized univariate score tests with high dimensional covariates

• Ching-Chieh 賴慶杰 (2020) Change point estimation based on copula-based Markov chain model for binomial time series data

• Xin-Wei Huang 黃昕蔚 (2019) Likelihood-based inference for copula-based Markov chain models for continuous, discrete, and survival data

• Yin-Chen Wang 王尹辰 (2019) A general class of multivariate survival models derived from frailty and copula models: application to reliability theory

• Ting-yu Lin 林庭羽 (2019) A shrinkage robust ridge estimator with an intercept term

• Jiung Huang Hsu 許竣瑝 (2019) Performance of a two-sample test with Mann-Whitney statistics under dependent censoring with copula models

• Wei-Ru Chen 陳韋儒 (2018) Copula-based Markov chain model with binomial data

• Chuang-Yan Huang 黃中彥 (2018) Likelihood-based analysis of doubly-truncated data under the location-scale and AFT models

• Wu Bo-Hong 吳柏宏 (2018) The Weibull joint frailty-copula model for meta-analysis with semi-competing risks data

• Zhisheng He 何致晟 (2017) Parametric likelihood inference with censored survival data under the COM-Poisson cure models

• Wei Lee 李威 (2017) Likelihood inference on bivariate competing risks models under the Pareto distribution

• Jia-Han Shih 施嘉翰 (2016) Dependence measures and competing risks models under the generalized Farlie-Gumbel-Morgenstern copula

• Yu-Ting Liao  廖昱婷 (2016) A review and comparison of continuity correction rules: the normal approximation to the binomial distribution

• Chi-Hung Pan 潘奇鴻 (2015) A copula-based parametric maximum likelihood estimation for dependently left-truncated data

• Ai-Chun Chen 陳愛群 (2015) A class of Liu-type estimators based on ridge regression under multicollinearity with an application to mixture experiments

• Szu-Peng Yang 楊思芃 (2014) A Class of Generalized Ridge Estimator for High-dimensional Linear Regression

• Ya-Hsuan Hu 胡雅萱 (2014), Maximum Likelihood Estimation for Double-truncation Data under a Special Exponential Family

• Yi-Ting Ho 何逸庭 (2014) A Robust Change Point Estimator for Binomial CUSUM Control Chart

• Fan-Hsuan Kao 高帆萱 (2013) An Improved Nonparametric Estimator of Distribution Function for Bivariate Competing Risks Model

• Shau-Kai Shiu 徐紹凱 (2013) Estimation and Model Selection for Left-truncated and Right-censored Data: Application to Power Transformers Lifetime Modeling

• Ting-Hsuan Long 龍庭軒 (2013) A Control Chart Based on Copula-based Markov Time Series Models

In the Institute of Statistical Mathematics (2023-)

• 2023: 多変量生存時間解析コース（短期集中研修） (10/20, 21; 11/3, 4)

In Hiroshima University (2024-)

• 2024: 生物・医療統計（集中講義） (11/19, 20, 26, 27)

In Kurume University (2021-)

• 2025 Fall: バイオデータモデリング (7/26, 8/2)

• 2025 Summer: Medical Statistics (台湾長庚大学生・夏季インターン向け講義) (7/24, 25, 28)

• 2025 Spring: バイオ統計基礎 (4/5, 4/11, 4/18)

• 2025 Spring: バイオインフォマティクスセミナー (4/12)

• 2024 Summer:  Survival Analysis with R  (台湾長庚大学生・夏季インターン向け講義)  (7/18, 19, 22. 23)

• 2024 Spring: バイオ統計基礎/バイオ統計数理 (4/6, 4/12, 4/19)

• 2024 Fall: バイオデータモデリング (8/31, 9/13)

• 2024 Spring: バイオ統計セミナーII (4/13)

• 2023 Fall: バイオデータモデリング (8/25,26, 10/7)

• 2023 Summer:  Modern Medical Statistics with R (台湾長庚大学生・夏季インターン向け講義)  (7/14, 7/24, 25, 26, 27, 28)

• 2023 Spring: バイオ統計基礎 (4/8, 14, 21), バイオ統計セミナーII (4/15, 5/20)　

• 2022 Fall: バイオデータモデリング（10/8,10/15,10/29,11/12,11/19）

• 2022 Summer: Basis Stat with R (7/14,19,20,21), Survival Analysis with R (7/28,29;8/2) (台湾長庚大学生・夏季インターン向け講義) 

• 2022 Spring:: バイオ統計基礎（4/23, 5/13, 5/20）、バイオインフォマティクスセミナー（5/21）、バイオ統計数理（6/10, 6/11, 6/18）

• 2021 Fall: バイオデータモデリング（8/28、9/12，10/2、11/6）、医学統計学（応用）（12/1, 2022/1/5, 1/19）

• 2021 Spring: バイオ統計基礎（4/23）、バイオインフォマティクスセミナー（5/22）

In Chang Gung University (2020-2021, 2023)

• 2023/12/25-29: R Shiny Web App (R Shiny 應用教學), a short course in Dept of Information Management

• 2020 Fall: Applied Statistics(應用統計) 

• 2020 Spring: Quality Management and Methods(品質管理與方法), Statistics II(統計學II)

In National Central University (2011-2019)

• 2019 Fall:  High-dimensional Data Analysis (多維度資料分析), Advanced Probability I (高等機率論Ｉ)  

• 2019 Spring: Statistical Computing I(統計計算Ⅰ)

• 2018 Fall : Quality Control(品質管制),  Special Seminar I(專題演講 I), Statistical Inference I (統計推論Ⅰ) 

• 2018 Spring: Survival Analysis I(存活分析Ⅰ), High-dimensional Data Analysis(多維度資料分析) 

• 2017 Fall: Mathematical Statistics (數理統計)   

• 2017 Spring: Survival Analysis I(存活分析Ⅰ), Quality Control (品質管制)

• 2016 Fall: High-dimensional Data Analysis (多維度資料分析), Statistical Inference III (統計推論 Ⅲ)

• 2016 Spring:  Survival Analysis I (存活分析Ⅰ),  Statistical Inference II (統計推論II) 

• 2015 Fall: Quality Control (品質管制),  Statistical Inference I (統計推論I)

• 2015 Spring:  Survival Analysis II(存活分析II) ,  High-dimensional Data Analysis(多維度資料分析)

• 2014 Fall: Quality Control (品質管制),  Survival Analysis I (存活分析Ⅰ)

• 2014 Spring: Mathematical Statistics II (數理統計II),  Advanced Probability I (高等機率論Ｉ) ,  Student Seminar I ( 書報討論Ｉ)

• 2013 Fall: Mathematical Statistics I (數理統計I)

• 2013 Spring: Quality Control (品質管制),  Statistical Inference II (統計推論II) 

• 2012 Fall:  Student Seminar I ( 書報討論Ｉ),  Statistical Inference I (統計推論I)

• 2012 Spring:  Student Seminar II ( 書報討論II),    Statistical Inference II (統計推論II) 

• 2011 Fall: Quality Control (品質管制),  Statistical Inference I (統計推論I)

In Japan Women's University (2010-2018)

• Statistics (統計学): a summer intensive class（2010/8, 2011/8, 2012/8, 2014/8, 2016/8, 2018/8）

In Kitasato University (2007-2008)

• 2007: Probability Theory (確率論), Statistics (統計学)

Past activities

1. Associate Editor, Heliyon, Quantitative biology, biotechnology and bioengineering (2022-2023)

2. Associate Editor, Heliyon, Bioinformatics and Computational Biology (2023-2025)

3. Associate Editor for Japanese Journal of Statistics and Data Science (JJSD) (2017-2023)

4. Guest Editor of JJSD Special Feature: Recent Statistical Methods for Survival Analysis (2020-2021) 

5. 日本統計学会誌　編集委員(2021-2024)

6. 計量生物学　副編集委員長 (2023-2025)

7. 学会誌「計量生物学45 巻 (2024) 1 号」：特集・生存時間データ解析法 ゲスト編集委員(2023-2024)

8. 学会誌「計量生物学45 巻 (2024) 2 号」：特集・生存時間データ解析法 ゲスト編集委員(2023-2024)

9. 日本統計学会誌 特集「生存時間解析・イベントヒストリー分析」編集委員(2021-2023)

10. Member of The Mathematical Society of Japan (2022/4/4~2023/3/31)

Organizer, Chair, Committee

• 2024/9-, Co-Chair, the 8th International Conference on Econometrics and Statistics (EcoSta 2025)  hosted by Waseda University, Tokyo, Japan, 21-23, August 2025

• Organizer & Chair of Invited Session, CO396: Survival analysis: Truncated data

• Organizer & Chair of Invited Session, CO319: Survival analysis: Censoring and competing risks

• CMStatistics 2024 (London), Scientific Program Committee

• 2024/9/2, International Journal: JJSD Session by JSPS KAKENHI Grant Number 24HP2004, 2024年度統計関連学会連合大会

• 2024/8/29, 医療健康データサイエンスセミナー 「Understanding Deep Neural Networks via Regression Modelling Approaches: Application of Biomedical Data」一般化線形回帰およびCox回帰モデリングによる深層学習の理解 ～医療データ応用例とPythonコードを通じて～ (オーガナイザー、司会)

• 2024 International Workshop on Statistical and Data Science -Survival and Correlated Data- 国際ワークショップ: 医療健康データの生存時間解析I,II, 写真付き報告

• 2024/7/16, 医療健康データサイエンスセミナー, 「Dynamic Risk Prediction Using Survival Tree Ensembles」イベントデータに基づく動的生存予測と医療データへの応用～決定木のアンサンブル法～ by Sy-Han Chiou (オーガナイザー、司会)

• 医療健康データサイエンスセミナー, 線形モデルにおける同時許容限界区間と医療・製薬における最適化の応答局面法 by 中村愛作先生 (オーガナイザー、司会)

• 2024/4/3, 医療健康データサイエンスセミナー, 「Optimal Multi-Stratum Factorial Designs with Applications to Medical and Health Data」実験計画法と医療健康データへの応用 by Prof. Ming-Chung Chang (オーガナイザー、司会)

• 第18回日本統計学会春季集会 企画セッション「生存時間解析・イベントヒストリー分析」 

• 短期集中研修2023: 多変量生存時間解析コース, 写真付き報告

• 2023/12/12, 医療健康データサイエンスセミナー,  Estimation of Causal Effects with Some Invalid Instrumental Variables and its Application to Medical and Health Data」因果効果の推定と操作変数 (オーガナイザー、司会), 統計数理研究所

• 2023 Survival Analysis for Medical and Health Data 国際ワークショップ: 医療健康データの生存時間解析 写真付き報告

• 2023信頼性研究会＠久留米大・医学部「情報通信システムの信頼性，信頼性一般」（会場世話人） 

• 2022年度計量生物セミナー「生存時間解析」（座長・オーガナイザー）：中央大学後楽園キャンパス12月8日・9日

• 2022信頼性研究会＠久留米大・福岡サテライト「情報通信システムの信頼性，信頼性一般」（会場世話人） 

• 2022統計関連学会連合大会、企画セッション：生存時間解析・イベントヒストリー分析（座長・オーガナイザー）

• 2021統計関連学会連合大会、企画セッション：生存時間解析のモデル・手法（座長・オーガナイザー）

• EcoSta 2022, Organizer & Chair of Invited Session, EO115: Methods for survival data analysis I

• EcoSta 2022, Organizer & Chair of Invited Session, EO139: Methods for survival data analysis II

• The 5th International Conference on Econometrics and Statistics (EcoSta 2022 in Kyoto), Scientific Program Committee

• CMStatistics 2019, Organizer & Chair of Invited Session, EO146: Multivariate survival models

• The 12th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2019) (in London), Scientific Program Committee

• CMStatistics 2018 (Italy), Organizer & Chair of Invited Session, EO332: Survival analysis and copula

• CMStatistics 2017 (London), Organizer & Chair of Invited Session, EO154: Survival analysis with dependent endpoints

• CMStatistics 2016 (Spain), Scientific Program Committee

• The 9th International Conference of the ERCIM WG on Computational and Methodological Statistics (CMStatistics 2016) (in Spain), Scientific Program Committee