Mathematics – Statistics Theory
Scientific paper
2006-04-03
Mathematics
Statistics Theory
University of Wisconsin-Madison Department of Biostatistics and Medical Informatics Technical Report
Scientific paper
We consider linear transformation models applied to right censored survival data with a change-point based on a covariate threshold. We establish consistency and weak convergence of the nonparametric maximum lieklihood estimators. The change-point parameter is shown to be $n$-consistent, while the remaining parameters are shown to have the expected root-$n$ consistency. We show that the procedure is adaptive in the sense that the non-threshold parameters are estimable with the same precision as if the true threshold value were known. We also develop Monte-Carlo methods of inference for model parameters and score tests for the existence of a change-point. A key difficulty here is that some of the model parameters are not identifiable under the null hypothesis of no change-point. Simulation students establish the validity of the proposed score tests for finite sample sizes.
Kosorok Michael R.
Song Rui
No associations
LandOfFree
Further details on inference under right censoring for transformation models with a change-point based on a covariate threshold does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with Further details on inference under right censoring for transformation models with a change-point based on a covariate threshold, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Further details on inference under right censoring for transformation models with a change-point based on a covariate threshold will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-444237