“Advanced Survival Analysis” is an online course offered at Statistics.com. Statistics.com is the leading provider of online education in statistics, and offers over 100 courses in introductory and advanced statistics. Courses typically are taught by leading experts. Some course highlights - A. Taught by renowned International Faculty (Not self-paced learning) B. Instructor led and Peer learning C. Flexible and Convenient schedule D. Practical Application and Software skills For more details please contact info@c-elt.com. Website: www.india.statistics.com

1. Online course
Advanced Survival Analysis
Taught by Prof. Matthew Strickland
(http://www.statistics.com/survival2/)
This course builds upon the statistical methods covered in the Survival Analysis course at
statistics.com. Discussion will focus on the extension of the Cox proportional hazards
model to (a) recurrent event survival analysis and (b) competing risks survival analysis.
The course will cover parametric survival models and frailty models and will conclude
with discussion on the relative merits of parametric vs. semi-parametric techniques for
modeling time-to-event data.
Who Should Take This Course:
Investigators designing, conducting or analyzing medical studies or clinical trials.
Researchers in any field (including engineering) working with data on how long things
last.
Course Program:
Course outline: The course is structured as follows
SESSION 1: Recurrent Event Survival Analysis
 The counting process approach for analyzing time-to-event data
 Survival curves for recurrent events
 Robust variance estimation
 Extension of the Cox proportional hazards model to accommodate recurrent
events
SESSION 2: Competing Risks Survival Analysis
 Options for modeling competing risks
 Discussion of the independence assumption
 Survival curves for competing risks
 Implementation of competing risks data in Cox proportional hazards models
using the Lunn-McNeil approach
SESSION 3: Parametric Survival Analysis
 Common distributions for time-to-event data (exponential, Weibull, log-logistic)
 The accelerated failure time model
 Parametric models for right-, left-, and interval-censored data
SESSION 4: Frailty (random intercept) Survival Analysis
 Purpose and assumptions of frailty models

2.  Incorporating frailties in parametric and semi-parametric survival analyses
 Discussion of the merits of parametric vs. semi-parametric survival models
Homework:
Homework in this course consists of short answer questions to test concepts, guided
data analysis problems using software and guided data modeling problems using
software.
Software:
The course will require participants to use a sophisticated statistical package (e.g., SAS,
STATA, R, or S+) to analyze survival analysis data. There will be illustrations and model
answers in SAS, R, Stata and SPSS.
Instructor:
The instructor, Matthew Strickland, is Assistant Professor in the Department of
Environmental and Occupational Health at Emory University. He has taught a variety of
in-person and distance education courses on Epidemiologic Modeling, Fundamentals of
Epidemiology, and Maternal/Child Health Epidemiology. His research interests are air
pollution epidemiology, birth defects epidemiology, and epidemiology methods.
This course takes place over the internet at the Institute for 4 weeks. During each course
week, you participate at times of your own choosing - there are no set times when you
must be online. The course typically requires 15 hours per week. Course participants will
be given access to a private discussion board so that they will be able to ask questions
and exchange comments with instructor, Prof. Matthew Strickland. The class
discussions led by the instructor, you can post questions, seek clarification, and interact
with your fellow students and the instructor.
For Indian participants statistics.com accepts registration for its courses at reduced
prices in Indian Rupees through us, the Center for eLearning and Training (C-eLT), Pune.
For India Registration and pricing, please visit us at www.india.statistics.com.
Email: info@c-elt.com
Call: +91 020 66009116
Websites:
www.india.statistics.com
www.c-elt.com