More about the webinar
As survival analysis is tied to the number of events that occur, power analysis will usually consist of both calculating the required number of events and the sample size expected to achieve that number of events.
This means there is significant flexibility required to deal with issues such as varying accrual, follow-up, hazard rate and dropout patterns even within the “standard” two independent group log-rank scenario.
One area of significant interest in recent years has been non-proportional hazards, where the hazard ratio varies over time, especially in the context of immunotherapies which commonly have a “delayed effect”.
Multiple proposals have emerged for the analysis of these complex survival datasets with the MaxCombo test being a leading tool for analyzing complex outcomes such as delayed effects.
In addition to these considerations, there has also been significant work to extend to other study designs such as one group, paired and factorial analyses.
In this webinar, we explore the important concept required for power calculations for survival analysis. We will also examine how to deal with the most common concerns and issues which can arise including non-proportional hazards.
