Overview

Course name: Survival Analysis

Instructor:

Xiao Song

Date: Fall, 2019

Course Description:

Methods for analyzing time-to-event data, including univariate parametric and nonparametric procedures, regression models, diagnostics, group comparisons, and use of relevant statistical computing packages.

Textbooks:

  • Required: Modeling Survival Data in Medical Research, Third Edition. David Collett. Chapman and Hall/CRC.

  • Optional:

  1. Applied Survival Analysis, Second Edition. David W Hosmer, Stanley Lemeshow and Susanne May. Wiley.

  2. Modeling Survival Data: Extending the Cox Model. Terry M. Therneau and Patricia M. Grambsch. Springer.

  3. Survival Analysis: Techniques for Censored and Truncated Data. John P. Klein and Melvin L. Moeschberger.

Software: SAS (For survival analysis, SAS start earlier and own much more functions than R)

Objectives:

  1. time-to-event data, describe different types of censoring, and describe algebraic relationships between probability density functions, survival functions, hazard functions and cumulative hazard functions.

  2. be able to compare survival functions between groups using parametric, nonparametric and semi-parametric techniques.

  3. be able to model survival time with continuous covariates.

  4. be able to assess the fit of a survival model.

  5. Basic design issues including power and sample size for survival analysis.

Last updated on Apr 23, 2020