Outline

Organizer: Research Center for Medical and Health Data Science, the Institute of Statistical Mathematics (MHDS-ISM) (統計数理研究所 医療健康データ科学研究センター)
Place:　The Institute of Statistical Mathematics, 10-3 Midori-cho,
　　　　Tachikawa, Tokyo 190-8562, Japan　　Access & MAP
Mode: In-person
Audience: accept pre-registered participants
Fee: free of charge

Registration

Pre-registration is required. Registration deadline is 2025-08-12 .

Abstract

  Survival analysis provides fundamental statistical methods for analyzing medical and health data. The 3rd edition of “International Workshop: Survival Analysis for Medical and Health Data” comes back to the MHDS-ISM in 2025. Prominent researchers of survival analysis from USA, Denmark, Taiwan, Korea, and Japan will present their novel statistical ideas. The workshop is not just a seminar but a milestone in the journey towards harnessing the full potential of statistics and data science, making it a turning point for anyone vested in the future of the world.

Agenda

13:10 Registration starts
13:30 Opening remarks
13:30 - 14:25 Session I: (Parametric models and inference)
Chair: Sy Han Chiou (Southern Methodist Univ, USA)
- Speaker 1 (25 min): Lachos Davila, Victor Hugo (Univ of Connecticut, USA)
- Speaker 2 (25 min): Nanami Taketomi (Nagasaki Univ, Japan)
Break
14:35 - 16:00 Session II: (Dependence modeling)
Chair: Ralf Andreas Wilke (Copenhagen Business School, Denmark)
- Speaker 1 (25 min): Li-Hsien Sun (National Central Univ, Taiwan)
- Speaker 2 (25 min): Sy Han Chiou (Southern Methodist Univ, USA)
- Speaker 3 (25 min): Takeshi Emura (Hiroshima Univ, Japan)
Break
16:10-17:00 Session III: (Competing risks)
Chair: Lachos Davila, Victor Hugo
- Speaker 1 (25 min): Ralf Andreas Wilke (Copenhagen Business School, Denmark)
- Speaker 2 (25 min): IL-Do Ha (Pukyong National Univ, South Korea)
17:00-17:10 Closing: Takeshi Emura (Hiroshima Univ, Japan)

Invited Speakers

Lachos Davila, Victor Hugo		The EM Algorithm in Mixture Cure Models with Arbitrary Survival and Link Functions
Nanami Taketomi		Shrinkage estimation for the rate parameter under the exponential distribution with censored survival data
Ralf Andreas Wilke		Proportionality and partial likelihood method in competing risks models
Sun, Li-Hsien		Change point analysis under a copula-based Markov model for Weibull time series
Sy Han Chiou		Analyzing bivariate survival data using pseudo-observations
Takeshi Emura		Inferring median survival under dependent censoring
IL-DO Ha		Robust estimation and frailty inference on competing-risks frailty models