**Lectures**: M, W 3:00-4:15pm, Riddick Hall 314. Syllabus

**Office Hours**: W 1:20-2:50pm, 5212 SAS
Hall (or by appointment)

**Textbooks (optional)**: *Counting
Processes and Survival Analysis *by Fleming and Harrington: Wiley
(1991).

**Reference Books**:

*The Statistical Analysis of Failure Time Data*by John D. Kalbfleisch and Ross L. Prentice (2002, 2nd Ed.)*Statistical Models Based on Couting Processes*by Andersen, Borgan, Gill and Kieding: Springer Verlag (1993).*Modeling Survival Data: Extending the Cox Model*by Terry M. Therneau and Patricia M. Grambsch (2000).

**Tenative****
Course Schedule**:

- Week 1 (Aug 20, 22): 1. Introduction to censored
survival data and associated basic quantities. 2. Competing risks and
cause specific hazards.
- Week 2 (Aug 27, 29): 3. Kaplan-Meier estimator,
Nelson-Aalen estimator, and their properties
- Week 3 (Sep 3, 5): No class (Sep
3, Labor Day Holiday; Note: there is also NO class on Sep 5)
- Week 4 (Sep 10, 12): Counting process and its theory
- Week 5 (Sep 17, 19): Counting process and its theory
- Week 6 (Sep 24, 26): Martingale process and martingale
central limit theorem
- Week 7 (Oct 1, 3): Lenglart's
inequality and confidence bands construction (Oct
3, in class mid-term exam)
- Week 8 (Oct 8, 10): Two sample nonparametric tests
- Week 9 (Oct 15, 17): Cox's proportional hazards
regression models
- Week 10 (Oct 22, 24): Survival
function estimation and simulation methods for confidence bands. Model
diagnostics using martingale residuals.
- Week 11 (Oct 29, 31): Additive hazards
model; linear transformation model;
- Week 12 (Nov 5, 7): cure rate model;
accelerated failure time model;
- Week 13 (Nov 12, 14): frailty model, WLW
method, recurrent event data
- Week 14 (Nov 19, 21): recurrent event data (Nov 21, Thanksgiving, NO class)
- Week 15 (Nov 26, 28): Nov 26, first student
presentation for final project (Nov 28, NO class)
- Week 16 (Dec 3): second student
presentation for final project

**Homework**:

- Homework 1
- Homework 2
- Homework 3
- Reading Assignment (Andersen and Gill, 1982, AOS)
- Homework 4
- Reading Assignment (martingale residual based
model diagnostics, additive hazards
model, linear transformation model and accelerated failure time model)
- Homework 5
- Reading Assignment (frailty model I, II, III, multivariate survival data (WLW method), and recurrent event data)

**Project Reading**:

- paper 1: Buckley-James
estimation for AFT model (Anran Wang)
- paper 2: Kernel
smoothing based efficient estimation for AFT model (Yichi Zhang)
- paper 3: Inverse probability censoring
weighted estimation for linear transformation model (Xiaofei Bai)
- paper 4: Induced smoothing
estimation for AFT model (Runchao Jiang)
- paper 5: Risk
prediction for censored regression models I (Eun
Jeong Min)
- paper 6: Risk
prediction for censored regression models II (Wei Xiao)
- paper 7: Risk prediction for
censored regression models III (Shikai Luo)

Basic
requirements for the project presentation: each person should prepare a talk
slide (no more than 20 pages), which should cover the following materials:

1. the
descriptions of the model and/or the problem of interest

2. the discussions of the
proposed method such as the motivation of the method, the key ideas and the
estimation procedure (this should be the focus of the
presentation)

3. the asymptotic properties
of the proposed estimators and their associated inference methods (if possible,
you may outline the key steps for establishing the asymptotic results, for
example, what techniques were used and what are the difficulties?)