Advanced Statistical Methods for Handling Event History Data: Going Beyond the Cox Model
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.
- 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
|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.
Get in Contact
Email Address: firstname.lastname@example.org
Manages all IHPME-wide communications and marketing initiatives, including events and announcements.