EVENT HISTORY & SURVIVAL ANALYSIS  NOW IN ITS TWENTY-FOURTH YEAR!  A Complete 5-Day Course on the Analysis of Longitudinal Event Data How to study the causes of Births and Deaths Marriages and Divorces Arrests and Convictions Job Changes and Promotions Bankruptcies and Mergers Wars and Revolutions Residence Changes Consumer Purchases Adoption of Innovations Hospitalizations For survival data, ordinary regression analysis won't do the job If you've ever used regression analysis on longitudinal event data, you've probably come up against two intractable problems: 1. Censoring: Nearly every sample contains some cases that do not experience an event. If the dependent variable is the time of the event, what do you do with these "censored" cases? 2. Time-dependent covariates: Many explanatory variables (like income or blood pressure) change in value over time. How do you put such variables in a regression analysis? Makeshift solutions to these questions can lead to severe biases. Survival methods are explicitly designed to deal with censoring and time-dependent covariates in a statistically correct way. Originally developed by biostatisticians, these methods have become popular in sociology, demography, psychology, economics, political science, and marketing. How you will benefit from this course Event History & Survival Analysis is a complete course covering both the theory and practice of survival methodology. In fact, it includes all the lectures and assignments in Professor Allison's one-semester course. Assuming no previous knowledge of survival analysis, this course will turn you into a knowledgeable and skilled user of these indispensable techniques. Here are a few of the skills you will acquire: How to organize survival data. How to choose the right time axis. When to use discrete vs. continuous time methods. How to handle left censoring. How to pick the right computer program. What to do about nonproportionality. How to compute R-squared. When and how to correct for unobserved heterogeneity. How frequently to measure independent variables. What to do if there is more than one kind of event. How to test for sensitivity to informative censoring. How to tell if a model fits the data Who should attend? If you need to analyze longitudinal event data and have a basic statistical background, this course is for you. You should have a good working knowledge of the principles and practice of multiple regression, as well as elementary statistical inference. But you do not need to know matrix algebra, calculus, or likelihood theory. Previous participants have come from a wide variety of fields: sociology, demography, psychology, economics, management, finance, history, marketing, biology, medicine, veterinary medicine and criminal justice. Computing At least one hour each day is devoted to carefully structured and supervised assignments on personal computers, with one computer for each participant.  Additional time is available for exploring other sample data sets. Or you can bring your own data and try out new techniques as you learn them. All assignments are done with the SAS statistical package.  SAS procedures used in the course include PHREG, LIFEREG, LOGISTIC, and LIFETEST.   Location, format, materials The course meets Monday through Friday at Temple University Center City, located in the heart of Philadelphia at 16th & Market Streets, across from City Hall. Here is a typical day's schedule: 9-12  Lecture 12-1  Lunch break 1-3    Lecture 3-5   Computing lab Participants will get a copy of  Professor Allison's text Survival Analysis Using SAS : A Practical Guide.  In addition, participants receive a 120-page manual containing detailed lecture notes (with equations and graphics), examples of computer printout, and many other useful features. This book frees participants from the distracting task of notetaking. Course outline 1. Fundamentals of survival snalysis 2. Weibull and Gompertz models 3. Types of censoring 4. Life table method 5. Kaplan-Meier method 6. Accelerated failure time models 7. Maximum likelihood estimation 8. Interpretation of parameters 9. Proportional hazards models 10. Partial likelihood estimation 11. Time dependent covariates 12. Competing risks 13. Discrete time analysis 14. Sensitivity analysis for censoring 15. Choice of time origin 16. Testing the proportional hazards assumption 17. Heterogeneity and time dependence 18. R-squared 19. Repeated events 20. Left censoring, left truncation Registration and Lodging The fee of $1400 includes all course materials and computing costs.  To ensure your participation, click here to register. Cancellations received two weeks before the course begins are fully refundable (minus a $100 processing fee if you paid by credit card).    Participants must make their own arrangements for lodging and meals. A block of rooms has been reserved at the Club Quarters Hotel at the rate of $114/night.  This hotel is a five-minute walk from the course location.  Comments by Recent Participants Participants in the July 2008 seminars were asked to rate the course on a scale of 1 (worst) to 10 (best).  The average score for 24 respondents was 9.1. They were also asked if they wished to make an attributed statement regarding the course. Here are all the comments that were received: “Of all the ways to pursue professional development, Dr. Allison’s course is unique in the attention it gives to theory, programming and interpretation of results.  Its week-long length gives me assurance that new knowledge will endure beyond the period of the course and confidence in using the methodology in my work place.” Robert Goldberg-Alberts, Wyeth Research   “Dr. Allison makes this complex subject matter extremely palatable with humor, real life data and anecdotal energy.  The materials provide thorough explanations of the method and serve as long term reference guides.” Robin Mekonnen, Children’s Hospital of Philadelphia   “This course is suitable for everyone interested in in-depth understanding of survival methods.  There is no doubt that this course improves the likelihood of success in publishing with these methods.” Ross Andel, University of South Florida   “Dr. Allison is wonderful, and the course was excellent with well-organized lecture notes.  Also, the hands-on sessions were very helpful to review and practice the contents covered each day.” Sungkyu Lee, University of Pennsylvania   “Most informative statistics workshop and great instructor who is inspiring.” Younghee Lim, Baton Rouge, LA   “The course is extremely comprehensive without compromising on clarity, and caters to a wide range of experience from graduate students to faculty and professionals.” Charlotte Gill, University of Pennsylvania   “If you find yourself in need of survival analysis and wish that you had taken such a course in school, well, this course will be great for you, perhaps a better choice than taking a semester-long course.  Dr. Allison is an excellent speaker and this course is very well organized.” Zhenqiu Lin, Yale University   “The course had the best assimilation of information on survival analysis for participants.  A quick but very clear and concise look into methods.” Leny Mathew, Philadelphia, PA   “Dr. Allison is not only knowledgeable in the survival methodology, he’s an excellent teacher.  The course covers fundamental concepts and builds up to advanced topics in logical transition.  Highly recommended.” Anne Jacobson, Siemens Healthcare Diagnostics   “This is the best course in survival analysis that combines mathematical background and real data applications.  I highly recommend the course with Professor Allison for anyone interested in survival analysis.” Nedaa Timraz, Georgetown University   “This ‘Survival Analysis Using SAS’ course is an excellent one, and is very well structured and lectured.  It not only covered many statistical theories but, more importantly, also covered very practical and important topics and examples on survival analysis.  I recommend this course to anyone who is interested in time-to-event analysis.” Shawn Du, University of Texas SPH at Houston