Extension of a Two-Stage Conditionally Unbiased Estimator of the Selected Population to the Bivariate Normal Case |
| |
| Authors: | Michael W. Sill Allan R. Sampson |
| |
| Affiliation: | 1. The GOG Statistical and Data Center, Roswell Park Cancer Institute , Buffalo, New York, USA;2. Department of Biostatistics , University at Buffalo , Buffalo, New York, USA msill@gogstats.org;4. Department of Statistics , University of Pittsburgh , Pittsburgh, Pennsylvania, USA |
| |
| Abstract: | A useful parameterization of the exponential failure model with imperfect signalling, under random censoring scheme, is considered to accommodate covariates. Simple sufficient conditions for the existence, uniqueness, consistency, and asymptotic normality of maximum likelihood estimators for the parameters in these models are given. The results are then applied to derive the asymptotic properties of the likelihood ratio test for a difference between failure signalling proportions between groups in a ‘one-way’ classification. |
| |
| Keywords: | Biased Bivariate normal distribution Clinical trial Conditional estimation Correlated observations Estimation after selection Maximum Ranking and selection Surrogate UMVUE |
|
|
