Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
1148002 | Journal of Statistical Planning and Inference | 2009 | 10 Pages |
Abstract
We consider asymptotic properties of the maximum likelihood and related estimators in a clustered logistic joinpoint model with an unknown joinpoint. Sufficient conditions are given for the consistency of confidence bounds produced by the parametric bootstrap; one of the conditions required is that the true location of the joinpoint is not at one of the observation times. A simulation study is presented to illustrate the lack of consistency of the bootstrap confidence bounds when the joinpoint is an observation time. A removal algorithm is presented which corrects this problem, but at the price of an increased mean square error. Finally, the methods are applied to data on yearly cancer mortality in the US for individuals age 65 and over.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ryan Gill, Grzegorz A. Rempala, Michal Czajkowski,