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, 2017      STA 709 - 001 Advanced Survival Analysis

Instructor: Dr. Mai Zhou

Office: MDS 343, Mailbox: MDS 307, Phone: 257-6912, E-mail: mai@ms.uky.edu, Web page (this page): http://www.ms.uky.edu/~mai/sta709.html
Office Hours:  by appointment.

Class: Mon/Wed/Fri  10:00 AM -- 10:50 AM at MDS 335.   First day of class Jan. 11. Last day of class April 28, 2017  

              MLK Day 1/16/2017  SpringBreak: 3/13 - 3/18

Textbook: My own Lecture Notes will be available in class.
Other useful materials may taken from the following books:  
For treatment of counting processes and martingales 
The Statistical Analysis of Failure Time Data 2nd Ed. by Kalbfleisch and Prentice (2002) [In particular, Chapter 5]  
For treatment of Empirical Likelihood:
Empirical Likelihood Method in Survival Analysis (2016) by Zhou.

Less relavant:
Counting Processes and Survival Analysis by Fleming and Harrington (1991) [this book contains all the details on counting process.But it is too big.]
For treatment of empirical processes
Convergence of Stochastic Processes. (1984) by Pollard. A PDF copy of the book.
Another paper by Pollard and Hjort, show CLT of an estimator defined by minimizer here


My older notes in the links below.

FirstDay and Outline

Weekly Topics:
Introduction. A brief review of sta 635 (Survival Analysis) 
Review of basic survival analysis. Identifiability of survival with independent censorshio model.
Power analysis of the log rank test.
Review of Poisson processes. Generalizations. Counting processes (see my notes above)
Uniform convergence of empirical processes.
The limit of stochastic processes, Brownian Motion, Brownian bridge, Gaussian processes. 
Counting processes. Martingales. Martingale CLT.
Integration of a martingale. Some basic formula/rules for variances.
The limit of a Nelson-Aalen estimator; Limit of the log rank test.
Empirical Likelihood method related to the Nelson-Aalen estimator.
The power of weighted log-rank tests. How to chose a test.
The limit of a Kaplan-Meier estimator. NPMLE, interval censored data, Self-consistency.
The CLT for the Cox proportional hazards regression model. Yang and Prentice generalization of
the Cox model.
The AFT model. R package rankreg

Introduction to the Empirical likelihood method. Empirical likelihood with censored data.
Wilks theorem for empirical likelihood ratio. 

Evaluations:  Homework will be assigned weekly in class.
Homework 35% 
Project + presentation 27%
Midterm Exam 18%
Final Exam 20%     

Some links:
My notes1.
My notes (on counting processes). on CLT.
The Nelson-Aalen estimator and Kaplan-Meier estimator is NPMLE KapNel1
Some extensions of Glivenko-Cantelli Theorem (look at Lemma 3 at the end) G-C1
Some uniform SLLN for Nelson-Aalen and Kaplan-Meier estimator for non-identically distributed case. G-C2
[try get the convergence rate for Kaplan-Meier estimator, iid case.]
My Note Two (on hazard integrals): 2.0  2.1  2.2
Empirical Likelihood (hazard)
Over determined estimating eq
A plot and the R code

Rcode#1
Rcode#2
Rcode#3

Over-determined Estimating Eq Example
Some old Homework and a brief answer.
Learn Counting Process in 25 Minutes!  (Web page with applet)
Kolmogorov-Smirnov Test
Some notes on Brownian Motion. More Brownian motion notes: 1, 2
Yet more Lecture Notes for Brownian Motion (120pages)   
One and Two dim Brownian Motion (Web page with applet)
Notes on AFT model and empirical likelihood will be distributed in class.
My own notes: Empirical likelihood with censored data
Owen's empirical likelihood talk.
Owen 1988BiometrkaPaper
My note on binomial EL

Make-up Policy for Missed Exams: Make-up quizzes and exams will be given only for university excused absences. Requests must be made at least one week prior to the exam, when possible, and must be approved. If you are unable to attend and exam due to unforeseen circumstances you must contact me or the department office (257-6115) as soon as possible (within 2 days). Absences due to illness must be documented by a clinic, doctor or hospital visit and a note of explanation. Late homework and computer assignments will be accepted only for university excused absences.