Date(s) - 06/23/2016 - 06/24/2016
Categories No Categories
Start Date: 6/23/2016
End Date: 6/24/2016
Courtyard Boston Downtown
275 Tremont Street
Taught by Paul Allison, Ph.D.
For event-time data, ordinary regression analysis wont do the job
If youve ever used regression analysis on longitudinal event data, youve probably come up against two intractable problems:
- 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?
- 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 seminar
Survival Analysis covers both the theory and practice of survival methodology. 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.
- 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.
This is a hands-on course with ample opportunity for participants to practice survival analysis.