Identification of Best Model to Fit the Chronic Kidney Disease Data Set

ChatGPT Log in You said: Uploaded image Convert it to document ChatGPT said: Here’s the transcribed and cleaned-up version of the text in the image as a document format: Abstract Chronic Kidney Disease (CKD) refers to the progressive loss of renal function. Chronic kidney disease (CKD) is a condition in which the kidneys are damaged and cannot filter blood as well as they should. There are many different methods used to conduct survival analysis. The models used in estimating survival analysis, which are log-normal and Weibull, were complementary and can be used in conjunction with each other. Other times, it often happens that two or more methods may seem attractive for a given analysis. The results obtained show that both of the distributions are best estimators and log-likelihood of the chronic kidney disease data. We conclude that the Weibull and log-normal distributions are the best estimators for chronic kidney disease data based on the results obtained. It is observed that the plot of survival function against time shows that the log-normal (AIC) function fitted the chronic kidney disease data better than the Weibull function, based on their criterion, i.e., AIC. Because the analysis conducted above shows that the Akaike Information Criterion (AIC) of the log-normal distribution has a minimum value of AIC compared to the Weibull distribution.