CANCELLED: Survival Analysis
Description: Settings in which the outcome is the waiting time to an event, such as time to death or time to disease diagnosis, are often encountered in clinical research. Analysis of such so-called survival data requires special statistical techniques to account for the longitudinal nature of data and the missingness issues arising when following patients incompletely over time. The present course is a case-based introduction to statistical methods for survival data.
Topics covered will include the following:
- Estimation of the survival function
- Risks vs rates
- Regression models for the rate, including Cox regression
- Regression models for the risk
- Competing risks
- Common biases in survival analysis and how to avoid them
The course includes computer practical exercises in a statistical software program such as Stata or R. Upon completion of the course, the student will be able to select, perform, and report statistical basic analyses involving survival time outcomes.
Literature: To be announced
Prerequisites: Knowledge of statistics and regression methods at the level of the ph.d. course "Regression I".
Evaluation: Written assignment
Organizer: Anders Gorst-Rasmussen, PhD, senior biostatistician
Lecturers: Anders Gorst-Rasmussen, PhD, senior biostatistician; Søren Lundbye-Christensen, PhD, senior biostatistician; others TBA
ECTS: 2,4 (3 days)
Time:
Place:
Zip code: 9000
City: Aalborg
Number of seats:
Deadline:
Important information concerning PhD courses
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.
Description: Settings in which the outcome is the waiting time to an event, such as time to death or time to disease diagnosis, are often encountered in clinical research. Analysis of such so-called survival data requires special statistical techniques to account for the longitudinal nature of data and the missingness issues arising when following patients incompletely over time. The present course is a case-based introduction to statistical methods for survival data.
Topics covered will include the following:
- Estimation of the survival function
- Risks vs rates
- Regression models for the rate, including Cox regression
- Regression models for the risk
- Competing risks
- Common biases in survival analysis and how to avoid them
The course includes computer practical exercises in a statistical software program such as Stata or R. Upon completion of the course, the student will be able to select, perform, and report statistical basic analyses involving survival time outcomes.
Literature: To be announced
Prerequisites: Knowledge of statistics and regression methods at the level of the ph.d. course "Regression I".
Evaluation: Written assignment
Organizer: Anders Gorst-Rasmussen, PhD, senior biostatistician
Lecturers: Anders Gorst-Rasmussen, PhD, senior biostatistician; Søren Lundbye-Christensen, PhD, senior biostatistician; others TBA
ECTS: 2,4 (3 days)
Time:
Place:
Zip code: 9000
City: Aalborg
Number of seats:
Deadline:
Important information concerning PhD courses
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.