Inference for Shift Functions in the Two-Sample Problem With Right-Censored Data: With Applications

Abstract

For two distribution functions, F and G, the shift function is defined by Δ(t) = G ⁻¹ · F(t) - t. The shift function is the distance from the 45° line and the quantity plotted in Q-Q plots. In the analysis of lifetime data, A represents the difference between two treatments. The shift function can also be used to find crossing points of two distribution functions. The large-sample distribution theory for estimates of Δ is studied for right-censored data. It turns out that the asymptotic covariance function depends on the unknown distribution functions F and G; hence simultaneous confidence bands cannot be directly constructed. A construction of simultaneous confidence bands for Δ is developed via the bootstrap. Construction and application of such bands are explored for the Q-Q plot.

Key Words:

• Bootstrap
• Censored data
• Crossing points
• Q-Q plots
• Shift function
• Treatment effect
• Two-sample problems