Survival Analysis using Modified Kaplan-Meier Model

Speakers: Prof. Eyitayo K Lasisi, Mr. Hamza Yusuf

• slides of Prof. Eyitayo K Lasisi
• slides of Dr. Hamza Yusuf
• Watch the recording

Abstract

Survival analysis, or more generally, time-to-event analysis, refers to a set of methods for analyzing the length of time until the occurrence of a well-defined end point of an interest. A unique feature of survival data is that typically not all patients experience the event (e.g, death) by the end of the observation period, so the actual survival times for some patients are unknown.  Appropriate analysis of survival data requires specific statistical methods that can deal with censored data. As the assessed outcome is frequently mortality, these techniques are subsumed under the term survival analysis. Kaplan Meier is a non-parametric statistic that deals with time-to-event data, which analyze the patients or participants that will be lost to follow-up or dropped out of the study; those who will develop the disease of interest or those that will survive it.  In this seminar, I will refresh our knowledge on Kaplan Meier model as a statistical model for survival analysis, identify various types of censoring in survival analysis, describe survival and hazard function in survival analysis and final introduce the modified model.