Rank Invariant Tests for Interval Censored Data under the Grouped Continuous Model

Abstract

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 proportional hazards. We frame the problem as a linear rank test of a shift 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 using the logistic error when the location shift assumption does not hold.