Which statement best describes a difference between Kaplan-Meier and the life-table approach?

• A. Kaplan-Meier uses intervals to group events; life-table estimates probability at each event time.
• B. Kaplan-Meier requires only cross-sectional data; life-table requires cohort data.
• C. Kaplan-Meier measures incidence; life-table measures prevalence.
• D. Kaplan-Meier ignores censoring; life-table accounts for censoring.

Answer: (C)

The main idea being tested is how time-to-event information and censoring are handled differently by Kaplan-Meier and the life-table method. Kaplan-Meier uses the exact times of each event and of censoring to update the survival probability at every observed event time, creating a stepwise curve that drops precisely when an event occurs and stays flat between events. Censoring is incorporated by reducing the number at risk after the time of censoring, without inserting a drop at the censoring time itself.

In contrast, the life-table approach groups data into fixed time intervals and estimates the probability of surviving through each interval, often assuming a roughly constant hazard within each interval. This means timing within an interval is not used, and censoring is handled within the interval counts rather than at exact event times, which can make the resulting curve less precise but easier to compute when only aggregated data are available.

Among the provided statements, the true distinction is not about incidence versus prevalence or about cross-sectional versus cohort data; it centers on time resolution and censoring. Kaplan-Meier relies on exact event times and proper censoring adjustments, whereas the life-table method relies on interval-based data and interval probabilities. In practice, Kaplan-Meier is preferred when exact event and censoring times are known, while the life-table approach is useful with summarized or interval data.