Applied Statistics

The purpose of this course is to provide students with the knowledge and tools to conduct a complete statistical analysis of survival data. By the end of the course, students should feel comfortable understanding and applying all commonly-used methods for survival data to data arising from a wide variety of disciplines. This class is ‘applied’ in that all techniques will be directly demonstrated on various survival datasets. The emphasis is on application of the concepts and ideas involved in data analysis and interpretation of results, rather than the underlying statistical theory. However, there will be some assumption of knowledge of some basic statistical concepts, such as distribution theory and linear regression. And there will be presentation of the prerequisite theoretical background for each technique discussed. The class is taught using SAS. Students will learn how to program every method discussed using SAS and be able to interpret all output for SAS procedures for basic survival methods.

In this course we will use the following methods for survival analysis:

• Kaplan-Meier Methods
• Life Table Analysis
• Parametric Regression Methods
• Cox Proportional Hazard Regression

STA532: Survival Analysis

Instructor: Dr. Randall H. Rieger

Office: 328 Anderson

Email Address: rrieger@wcupa.edu

Office Telephone: (610) 436-2893

Office Hours: Monday 3:30-5:30, Tuesday 3:30-5:30, Wednesday 3:00-4:00

Required Text

• Allison,, Survival Analysis Using SAS A Practical Guide, SAS Press, 1995
• Machin, Cheung, and Parmar, Survival Analysis A Practical Approach, 2nd edition, Wiley, 2006

SAS Software

The SAS Statistical software package is available free to any West Chester University student. The software can be loaded from a DVD onto a student's PC. The method of distributing the DVD’s to interested students will be discussed on the first day of class. As part of the licensing agreement, upon graduating from or leaving WCU, the software will expire and no longer be available for the student's use. In addition, the SAS software (and other statistical packages) will be available on all computers in the Applied Statistics Laboratory.

Course Objectives

The purpose of this course is to provide students with the knowledge and tools to conduct a complete statistical analysis of survival data. Students will get experience using common methods for survival analysis, including Kaplan-Meier Methods, Life Table Analysis, parametric regression methods, and Cox Proportional Hazard Regression. In short, by the end of the course, students should feel comfortable understanding and applying all commonly-used methods for survival data to data arising from a wide variety of disciplines. This class is ‘applied’ in that all techniques will be directly demonstrated on various survival datasets. The emphasis is on application of the concepts and ideas involved in data analysis and interpretation of results, rather than the underlying statistical theory. However, there will be some assumption of knowledge of some basic statistical concepts, such as distribution theory and linear regression. And there will be presentation of the prerequisite theoretical background for each technique discussed. The class is taught using SAS. Students will learn how to program every method discussed using SAS and be able to interpret all output for SAS procedures for basic survival methods.

Evaluation

Assignment	% of Grade
Exam 1 (written, in-class)	40%
Exam 2 (data analysis and report)	50%
Participation	10%

Class Format:

Most classes will consist of

• a lecture/presentation introducing new material
• a "LAB" assignment to be completed in class

• All homework assignments, lecture notes, and LAB assignments will be made available prior to class on the class blackboard web page.
• We will work with several datasets in this class.
1. A variety of datasets from Allison will be used in all in-class examples.
2. A primary dataset will be used in all of the lab exercises (CIRR.SAS7BDAT) to demonstrate the techniques considered in class.
3. The third dataset (WHAS.SAS7BDAT) will be used for the Final Exam.
• EXAM I will be a written, in-class examination. It will be announced two classes (one week) ahead of time.
• For EXAM II, students will be required to complete a thorough survival analysis of a dataset and write a report detailing the findings. It will be due on the last day of class. The assignment will be distributed within the first 2 weeks of class.
• On the take-home examination assignment, students must work independently on this assignment, under the guidelines of the Honor Code. If you have questions about the homework, Dr. Rieger will be glad to help you. No late assignments will be accepted.
• Missed exams can only be made up with a valid, verifiable, written university-approved excuse and must be made up within a week of the originally-scheduled exam.

Class Rules

• Students engaging in disruptive behavior will be dealt with according to university policy. Students are encouraged to consult the undergraduate catalog for details of this policy
• Academic dishonesty will not be tolerated in this class. Any cases of academic dishonesty will be dealt with according to university policy, and I will recommend the maximum possible penalty.
• Students with disabilities are encouraged to make their needs known to the instructor and the Office of Educational Accessibility early in the semester.
• Please make use of office hours and other department and university resources if extra help is needed.
• Students should bring a storage device to each class to save any relevant lab work.

Assignments

Notes: Assignments and (especially exams) are subject to revision and re-scheduling.

All exam dates should be considered tentative.

Class	Chapter(s)	Topics	Date
1	1 & 2	Class Overview Introduction to Survival Analysis Censoring Hazzard Function	May 29
2	2 & 3	Survival Curves	June 5
3	3	Comparing Survival Curves Kaplan-Meir Method Log Rank and Wilcoxon Test PROC LIFETEST	June 7
4	4	Life Table Methods Introduction to Parametric Regression Methods PROC LIFEREG	June 12
5	4	Parametric Regression Methods (cont'd)	June 14
6	5	Introduction to Cox Proportional Hazard Regression	June 19
7	5, 6	Cox Proportional Hazard Regressions	June 21
8	6	Cox Proportional Hazard Regressions	June 26
9	?	Additional topics: Discrete Time Data, Sample Size Determination, Competing Risks	June 28

There will be no class on May 31. 

There AMY be an option class on June 29th.