Final answer:
Kaplan-Meier curves are used to analyze time-to-event data, such as survival times. Comparing time-to-event curves allows us to estimate the probability of an event occurring at a specific time. The Kaplan-Meier method provides a more accurate representation of the survival experience over time, especially when there are censored observations.
Step-by-step explanation:
Kaplan-Meier curves are used to visualize and analyze time-to-event data, such as survival times or failure times. When comparing time-to-event curves, we are interested in estimating the probability of an event occurring at a specific time. This is different from comparing means, which focus on the average value of a variable. Comparing the means of curves may not be appropriate because the underlying data may not follow a normal distribution, which is required for comparing means.
The Kaplan-Meier method allows us to estimate the survival probability at each event time point, taking into account the censoring of data. It provides a more accurate representation of the survival experience over time, especially when there are censored observations (i.e., events that have not yet occurred). By comparing the survival curves, we can understand how different factors or treatments affect the probability of an event occurring.
For example, let's say we want to compare the survival rates of two different cancer treatment groups. We would plot the Kaplan-Meier curves for each group and compare their shapes and estimated survival probabilities at specific time points. This would give us a better understanding of how the treatments impact the survival outcomes, rather than simply comparing the means of the survival times.