I will try my best to make this page as accurate as possible but any changes in assignments, due dates, or anything else reported in class will take precedence, whether they are reflected in these pages or not. Your responsibilities are as they are reported in class.

Spring, 2009      STA 695 - 001 Topics in Survival Analysis and Empirical Likelihood

Instructor: Dr. Mai Zhou

Office: P. O. T. 849, Mailbox: P. O. T. 843, Phone: 257-6912, E-mail: mai@ms.uky.edu, Web page (this page): http://www.ms.uky.edu/~mai/sta695.html      Office Hours: Wed. 4 to 5PM or by appointment.

Class: Tuesday and Thursday

Textbook: Survival Analysis Using SAS   by  P. Allison  (especially the SAS code examples there)
The following notes may be useful:  Summary Notes on Survival Analysis by M. Wang
Survival Analysis Computations in R: Note1

Homework1 and 2 and 3,
Homewor4 and 5.
Homework 6 and 7

Reading assignment:  Understanding the Cox model

A document and examples for Cox model in SAS

Possible Projects

TakehomeFinal

Some other random Notes:

The Nelson-Aalen estimator and Kaplan-Meier estimator is NPMLE: Note2
more Notes to follow.

Notes on AFT model and empirical likelihood will be distributed in class.

PowerPoint File in Chinese on drug testing.

Introduction to the Empirical likelihood method. Empirical likelihood with censored data.
Wilks theorem for empirical likelihood ratio. (Notes will be available on above two.) 

Summary Notes on the R package emplik

Evaluations:  

For people who already took sta 635, there will be an extra class presentation and a different set of homework+ project .

Homework + a project 50%
Midterm Exam 20%
Final Exam 30%    Wed. May 6, 2009

Topics to be covered:   (Course Description)

Review of Exponential random variables, hazard function.

Piecewise exponential random variable. 

Parametric MLE, Fisher Information. Review of MLE theorey.

Randomly Censored data. MLE. Identification of Survival function in nonparametric setting. Parametric AFT models.

Kaplan-Meier estimator, Nelson Aalen estimator, Greenwood formula.

Confidence intervals.

Log-rank test. EL test.

Cox PH regression model. Semiparametric AFT models.

Counting processes, Martingales, Browning Motion, Browning Bridge.

A Central Limit Theorem for Poisson Processes/Counting process Martingales.

The martingale representation of Nelson-Aalen, log-rank test and Kaplan-Meier estimators.

The martingale representation of the Cox estimator.

Empirical Likelihood: Applications. R package emplik. (Notes?)

Applet which you can zoom in to look at the path of a Brownina motion

The self-similar property of a fractal

Two and one dimension Brownian motion

Additional topic for those already have sta 635: The variance of a Kaplan-Meier mean integral. Its estimation.

Introduction to Brownian Motion (LaTeX, Notes. This is one assignment to those that took sta 635)

Multivariate CLT for integrated Poisson processes/counting processes. (LaTeX, Notes. Dido)