EVENT HISTORY & SURVIVAL ANALYSIS  NOW IN ITS TWENTY-THIRD 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. The course comes in two flavors, SAS®  and Stata® . The SAS®  version of the course will utilize the PHREG procedure for proportional hazards modeling. This state-of-the-art program has many features found nowhere else, including vastly improved algorithms for handling discrete-time data and time-dependent covariates. You will learn how to make optimal use this procedure, as well as the LIFEREG, LOGISTIC, and LIFETEST procedures. Together, these programs make SAS® an excellent statistical environment for doing survival analysis. The second session of the course will use Stata for examples and assignments.  Here are some of the Stata commands that will be covered in the course: ltable for life table analysis stset for defining a survival analysis data set sts list for Kaplan-Meier estimation sts graph for plotting survival, cumulative hazard and hazard functions sts test for log-rank and Wilcoxon tests streg for parametric regression models stcox for Cox regression models stcurve for plots based on parametric or Cox regression models cloglog for discrete-time hazard models. Location, format, materials The course meets Monday through Friday at Temple University Center City, located in the heart of Philadelphia at 16th St.and J.F.K. Blvd. Here is a typical day's schedule: 9-12  Lecture 12-1  Lunch break 1-3    Lecture 3-5   Computing lab Participants in the SAS version of the course will get a copy of  Professor Allison's text Survival Analysis Using SAS : A Practical Guide.  Participants in the Stata version will get a copy of his text, Event History Analysis.  In addition, all 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 $1300 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. Special reduced rates have been arranged at  a nearby hotel: Comments by Recent Participants Participants in the July 2007 seminars were asked to rate the course on a scale of 1 (worst) to 10 (best).  The average score for 52 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: SAS Course “Professor Allison succinctly married a theoretical exposition of survival analysis with practical examples of its application.  I will definitely recommend the course.” R. Wesley Nimon, U.S. Navy “Fast-paced but extremely well organized and DEFINITELY worth attending.  This course gave me valuable insight into which methods to apply in situations specific to my company.  Time and money well spent!” Peter von Kamecke, IDEXX Laboratories “This is a good entry level course for people who are new to survival analysis.  Cross-area examples really help understand and apply theories.  The SAS programs are good and quick reference for further application.” Zhengrong Li, Merck & Company “Contents are clearly outlined in notes and presented in lectures, which give me a very good starting point for applying survival analysis in real business environments.  Highly recommended!” Clay Duan, Sears Holdings “A top-notch course which will have a great positive impact on the quality of my thesis.  The sessions and programming hours are packed with useful tips and information.  Highly recommended!” Philip Kappen, Stockholm University “This is one of the better statistical courses that I have attended.  The material was presented in a useful, practical way.  Dr. Allison is a good teacher and an experienced statistician.” Athula Abeyratne, Medtronic Inc. “An excellent introduction to the theory and practice of survival analysis.  I feel well-equipped to deal with different types of data and analysis issues.” Dawn Alley, University of Pennsylvania “This is a very good short course.  I learned a lot.  It will be very useful for my job.” Lisa Ying “This course was extremely useful.  I would recommend it to any individual who is concerned about the timing of events in various industries.  Absolutely excellent!!” Billal Karriem, Inductis   Stata Course   “This course is an effective, in-depth introduction to survival analysis.  Professor Allison is a knowledgeable and patient instructor.  I will apply the skills I gained this week to further my research.” Yvon Pho “I’ve found the course extremely useful.  Given its length, it was surprisingly comprehensive and covered each of the models with the discussion of assumptions, estimation, and problems that may arise.” Goulnar Kasymjanova “I enrolled in this course specifically to understand under what conditions particular models should be applied.  I did not need the amount of theory statisticians need, but enough to confidently choose the appropriate model in a variety of situations, and the ability to perform these models in a software package.  I feel these objections have been met with this class.” Heather Campbell, VA Cooperative Studies Program   “This course should be very helpful for those in education research, which has become increasingly quantitative since the advent of No Child Left Behind and, in particular, the call for evidence-based policy.  There are a variety of applications for which survival analysis can be used in the field, including formulating teacher retention policies (e.g., "merit pay" issues) and analyzing student time-to-graduation/degree at the secondary and postsecondary levels.  Although I had read about these techniques in textbooks, I greatly benefited from having an experienced guide in the instructor, who could point out the strengths, weaknesses and differences of opinion that exist in the field.  I certainly expect to use what I have learned from the course in my work at the U.S. Department of Education.”  Andrew Abrams, Office of Planning and Evaluation