stats262 - Survival Analysis

Instructors:
 J. Taylor
Sequoia Hall #137
jonathan.taylor@stanford.edu
723-9230

K. Cobb
HRP Redwood T211
kcobb@stanford.edu
723-9230
Schedule:
 T 10:00-1:00
Location:
 NOTE: ROOM CHANGED FROM LAST WEEK!!!!
HRP Redwood T138!
Office Hours:
 F 10:00-12:00 (Taylor)
M 2:00-4:00 (Cobb)
Textbook:
 Applied Survival Analysis . Hosmer & Lemeshow
Optional books:
 Survival Analysis Using the SAS System: A Practical Guide. Allison
Computing
environments:
 SAS, R
Tentative schedule
by week:
  1. Introduction, Regression
  2. Regression, ANOVA, Random Effects
  3. Mixed Effects, GLM
  4. Survival Data, Survival Functions
  5. Kaplan-Meier, Hazard Estimation, Log-Rank Tests
  6. Parametric Survival Models
  7. Cox Model
  8. Cox Model: Diagnostics, Selection
  9. Cox Model: Time Dependent Covariates
  10. Further Topics
TAs:
 Eric Bair: ebair@stanford.edu
Office Hours: Th 1:30-3:30, Clark Center S264

Pei Wang wp57@stanford.edu
Office Hours: Th 3:00-5:00, Sequoia Hall #223A


General Outline:
 By the end of the course students should be able to:
  1. Fit and interpret multiple linear regression models.
  2. Fit and interpret logistic and log-linear regression models.
  3. Assess the validity of linear, logistic and log-linear regression models.
  4. Compute descriptive statistics from lifetime data.
  5. Estimate the Kaplan-Meier curve, and Nelson-Aalen hazard estimate.
  6. Compare the survival curves of two populations.
  7. Fit a Cox proportional hazards model to lifetime data.
  8. Interpret the results of the Cox model.
  9. Assess the validity of the assumptions of the Cox model.
Evaluation:
  • 6 (short) assignments: 60%
  • take home final exam or project (to be discussed with instructors) : 40%
Assignments:
Notes:
Labs / Code: