A pilot study was designed to evaluate the potential efficacy of a program designed to reduce prison recidivism amongst inmates who have a documented long-term history of drug and/or alcohol problems. A sample of 11 prisoners was followed for up to 24 months after their most recent release from prison. Six of the inmates returned to prison at 3, 7 9, 11, 14 and 21 months respectively. Five of the inmates had not returned to prison as of the last time they were last contacted which was at 4, 8, 16, 24, and 24 months respectively.

Use the Kaplan Meier approach to estimate the survival curve for this set of inmates (which tracks the proportion who have not yet returned to prison over time). It will be helpful to construct a table like the ones appearing in lecture 5: however, all you will need to report in the quiz generator are certain quantities from this table for specific times.

-Why does the Kaplan-Meier curve not reach 0% in the follow-up period?

a. This is a trick question: the KM curve does reach 0%.

b. Because there is no censoring in these data.

c. Because the largest time values are censoring times.

d. Because the largest time values are event (prison return) times.