Sequential Test for Censored Data with Linear Transformation Models
by
Lin Huang
Columbia University
Coauthors: Zhezhen Jin

In this talk, we will present a sequential test for censored data with linear transformation models which include Cox proportional hazards model and proportional odds model. The approach is based on a score process motivated by Chen, Jin and Ying's (2002) estimation procedure. We show that for given interim analyses time points, the score process is approximated by a mean 0 multivariate normal distribution and the covariance matrix can be consistently estimated. Then with the boundaries procedure proposed by Slud and Wei (1982), a repeated significant test can be conducted. Numerical studies will also be presented.

Date received: March 22, 2007