Survival analysis using censored lung cancer data: A preliminary study

• Published in: AIP Conference Proceedings
• Main Author: Jamil S.A.M.; Ali N.I.; Mansor M.M.; Ul-Saufi A.Z.; Shafi M.A.
• Format: Conference paper
• Language: English
• Published: American Institute of Physics 2024
• Online Access: https://www.scopus.com/inward/record.uri?eid=2-s2.0-85203172383&doi=10.1063%2f5.0224907&partnerID=40&md5=15268780d6378cf83ef0dcc3d67704e3

The primary goal of Exploratory Data Analysis (EDA) is exploring and understanding data in order to gain insights and guide for further analysis. It allows for data cleaning which involves removing redundancies, handling missing values, correcting errors and transforming data if necessary as it is an important part of overall data preparation process. The aim of this study is to conduct a preliminary study before applying the survival method of analysis to censored lung cancer observations. The Kaplan-Meier survival curve, proportional hazard assumption, time varying covariate assumption via Scaled Schoenfeld residuals, Cox-Snell residuals for overall goodness of fit of the model assumption, and normality assumption via quantile-quantile (Q-Q) plot were all used in this study. The study discovered that the lung cancer censored observations were not violated with the parametric assumption among semi-parametric, and non-parametric assumptions. Thus, future work is recommended to include a comparison of the parametric method of survivals using the lung cancer data. The application of survival analysis would be ambiguous and mislead the researcher if the fundamental part of survival being left out. As a result, this study may aid in identifying appropriate assumptions for prior application on the survival analysis of censored observations. © 2024 Author(s).