Sample Size For Survival Analysis

About the webinar

Determining the appropriate number of events needed for survival analysis is a complex task as study planners try to predict what sample size will be needed after accounting for the complications of unequal follow-up, drop-out and treatment crossover.

Sample Size For Survival Analysis:
A guide to planning successful clinical trials

In this free webinar you will learn about:

Pairing study design with your calculation
Choosing the appropriate design and model to suit your survival study
Overcoming the challenges of survival analysis
The impact of unequal follow-up, varying hazard rates, dropout and more
The new flexible approaches for survival analysis:
How adaptive design and assurance could help with planning your survival study
Worked examples will include:
- Sample Size for the Log-Rank Test
- Group Sequential Design for Survival Data
- Sample Size Re-Estimation for Survival Data
- Bayesian Assurance for Survival Data

The statistical, logistical and ethical considerations all complicate life for biostatisticians as issues to balance in planning a survival analysis. However, this complexity has created a need for new analyses and procedures to help the planning process for survival analysis trials.

The wider move from fixed to flexible designs has opened up opportunities for advanced methods such as adaptive design and Bayesian analysis to help deal with the unique complications of planning for survival data but these methods have their own complications that need to be explored too.