Stanford Root

Schedule

Stanford Root

Schedule

BMDS 252

Survival Analysis (STATS 331)

UNITS:3
GRADING:Medical Option (Med-Ltr-CR/NC)
LEVEL:Graduate
GER:—

The course introduces basic concepts, theoretical basis and statistical methods associated with survival data. Topics include censoring, parametric model for survival time, Kaplan-Meier estimation, logrank test, proportional hazards regression, restricted mean survival time, survival analysis in group-sequential clinical trial, and extensions such as competing risk, multivariate survival time and recurrent event data. The traditional counting process/martingale methods as well as modern empirical process methods will be covered. The course will focus on providing methodological basis of survival analysis. Prerequisite: Understanding of basic probability theory and statistical inference methods.

Syllabus for selected term:
View Winter 2027 Syllabus

Sections

1 Term
Lecture 1Open
ID: 23455
0 / 30 enrolled
DAYS:Tuesday, Thursday
TIME:11:30 AM – 12:50 PM
LOCATION:TBD
INSTRUCTOR:
Shih, Mei-Chiung, Tian, Lu, Bi, Dehua, Lu, Ying
3units

BMDS 252: Survival Analysis (STATS 331)

3 units · Medical Option (Med-Ltr-CR/NC)

The course introduces basic concepts, theoretical basis and statistical methods associated with survival data. Topics include censoring, parametric model for survival time, Kaplan-Meier estimation, logrank test, proportional hazards regression, restricted mean survival time, survival analysis in group-sequential clinical trial, and extensions such as competing risk, multivariate survival time and recurrent event data. The traditional counting process/martingale methods as well as modern empirical process methods will be covered. The course will focus on providing methodological basis of survival analysis. Prerequisite: Understanding of basic probability theory and statistical inference methods.

Offered in Winter 2027 at Stanford University.

Winter 2027 sections

  • Lecture — Tuesday Thursday 11:30 AM – 12:50 PM — Shih, Mei-Chiung, Tian, Lu, Bi, Dehua, Lu, Ying (Graduate)

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