Advanced Statistical Methods for Handling Event History Data: Going Beyond the Cox Model
Aim
The aim of this workshop is to provide the Investigator with information on various methodological options that are available when examining time-to-event data. Researchers will see how to go beyond the Cox model for handling time to recurrent events, competing events, and multistate events.
Outline
- Define event history data: survival data, competing risks data, recurrent event data, multi-state data
- Review numerous examples of how such types of data arise in clinical and health services research.
- Discuss the relationship between multi-state data and …
- Time-to-event data
- Competing risks data
- Recurrent event data
- Introduce multi-state models, definition, notation, and assumptions (Markov and Semi-Markov)
- Data structure for multi-state models
- How to conduct a multi-state analysis without covariates
- Incorporating covariates
- How to conduct a multi-state analysis with covariates
- Competing risks data analysis using multi-state models
- Recurrent event data analysis using multi-state models
- How to handle common limitations in longitudinal observational data, such as intermittent observation and interval-censoring
| Date | January 30, 2015 |
| Time | 9 am to 3/4 pm (Lecture begins 10 am) Breakfast and lunch included |
| Location | MaRS Discovery District 101 College Street, South Tower Room CR-3 |
| Registration | Complimentary registration for IHPME faculty and postdoctoral fellows Maximum registration: 30 Registration is Closed |
Sign up for IHPME Connect.
Keep up to date with IHPME’s News & Research, Events & Program, Recognition, e-newsletter.
Subscribe to Connect Newsletter
Get in Contact
Communications
Marielle Boutin
Email Address: ihpme.communications@utoronto.ca
Manages all IHPME-wide communications and marketing initiatives, including events and announcements.