Which of the following methods is commonly used for survival analysis?

Kaplan-Meier analysis is a statistical method specifically designed for survival analysis, which deals with time-to-event data. This technique is used to estimate the survival function from lifetime data. It is particularly useful in clinical studies where the time until an event, such as death or disease occurrence, is of interest. The Kaplan-Meier method allows researchers to calculate the probability of survival at different time points and to visualize the survival curve, often enabling comparisons between different groups.

The other methods mentioned, while valuable in their own contexts, are not suitable for survival analysis. Logistic regression is used for binary outcome variables, factor analysis is a technique used to identify underlying relationships between variables, and linear regression models the relationship between a dependent variable and one or more independent variables in a continuous context. These methods do not address the specific needs of analyzing time-to-event data, such as censoring, which is inherent in survival studies. Thus, Kaplan-Meier analysis stands out as the appropriate choice for survival analysis.