RANK INVARIANT TESTS FOR INTERVAL CENSORED-DATA UNDER THE GROUPED CONTINUOUS MODEL

This paper creates rank invariant score tests for grouped or interval censored data. This generalizes Finkelstein (1986, Biometrics 42, 845- 854), who derived score tests for interval censored data assuming prop ortional hazards. We frame the problem as a linear rank test of a shif t in location with a known error distribution. We discuss adjustments to the test that may be required when the number of observation times is large. We offer a graphical test of the assumption of the location shift model and discuss an alternative interpretation of the test usin g the logistic error when the location shift assumption does not hold.