ACST840 Project 1: Kaplan-Meier Estimator Survival Analysis

This project examines the Kaplan-Meier Estimator (KME), a nonparametric method used for estimating survival distributions, particularly in the presence of censored data. The assignment begins with an introduction to survival analysis, defining the concept of survival functions and the challenges posed by censored data, where the exact time of an event is unknown. The core of the project is the KME, detailing its function and the assumptions it operates under. It explains how KME calculates the probability of survival over time, with detailed steps of how to compute probabilities using formulas and excel. The project then illustrates the application of KME through a sample dataset of patients undergoing treatment, calculating the survival probability at various time points. The analysis includes a step-by-step guide to the calculation process and demonstrates the estimation of survival probabilities. Finally, the project discusses the strengths and weaknesses of the KME, including its descriptive nature, its inability to handle time-dependent variables, and its failure to control for covariates. The conclusion emphasizes the importance of KME in survival analysis, its ability to account for unavailable subjects, and its usefulness in estimating time-defined probabilities.