Inference for shift functions in the two-sample problem with right-censored data: With applications

Henry H.S. Lu, Martin T. Wells, Ram C. Tiwari

Research output: Contribution to journalArticlepeer-review

14 Scopus citations

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.

Original languageEnglish
Pages (from-to)1017-1026
Number of pages10
JournalJournal of the American Statistical Association
Volume89
Issue number427
DOIs
StatePublished - 1 Jan 1994

Keywords

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

Fingerprint

Dive into the research topics of 'Inference for shift functions in the two-sample problem with right-censored data: With applications'. Together they form a unique fingerprint.

Cite this