Subject: STA 222
Title: Biostatistics, Survival Analysis
Units: 4.0
School: College of Letters and Science LS
Department: Statistics STA
Effective Term: 2002 Fall
Learning Activities
- Lecture - 3.0 hours
- Discussion/Laboratory - 1.0 hours
Description
Incomplete data; life tables; nonparametric methods; parametric methods; accelerated failure time models; proportional hazards models; partial likelihood; advanced topics.
Prerequisites
STA 131C
Cross Listed
Same course as BST 222.
Expanded Course Description
Summary of Course Content:
Introduction: (1 lecture); Incomplete Data (2 lectures): different types of censoring, truncation and biased data, survival and hazard function; Life Tables (2 lectures): demographic and actuarial methods, centralized mortality rate, smoothing of life tables; Nonparametric Methods (5 lectures): Kaplan-Meier, Lebesgue-Stieltjes integral, hazard estimation, nonparametric inference; Parametric Models (5 lectures): Weibull, Gamma and Gompertz models, maximum likelihood inference, diagnostics; Accelerated Failure Time Models (3 lectures): parametric version, frailty and random effects; Proportional Hazards Models (3 lectures): parametric versions, Cox model, diagnostics; Partial Likelihood (2 lectures): inference in Cox model, estimation of nonparametric component; Advanced Topics (5 lectures) Selections from: Proportional odds model and other semiparametric regression models, nonparametric regression methods with incomplete data, length biased data, counting process approach, advanced diagnostics; Exams and Review (2 lectures).
Illustrative Reading:
The course material is extracted from a variety of sources, including journals such as Biometrics, Biometrical Journal, Biometrika, Statistics in Medicine, JASA, Applied Statistics, and the New England Journal of Medicine. Relevant reference books are: Collett, D. Modelling Survival Data in Medical Research. Chapman and Hall, 1994. Harrington, D. and D. Fleming. Counting processes in Survival Analysis. Wiley, 1991. Klein, J.P., and M.L. Moeschberger. Survival Analysis. Springer, 1997.
Potential Course Overlap:
None