Journal of Applied Mathematics and Decision Sciences 
Volume 2007 (2007), Article ID 86180, 23 pages
doi:10.1155/2007/86180
Research Article

On the Semiparametric Efficiency of the Scott-Wild Estimator under Choice-Based and Two-Phase Sampling

Alan Lee

 Department of Statistics, University of Auckland, Auckland 1142, New Zealand
Received 30 April 2007; Accepted 8 August 2007

Recommended by Paul Cowpertwait

Abstract

Using a projection approach, we obtain an asymptotic information bound for estimates of parameters in general regression models under choice-based and two-phase outcome-dependent sampling. The asymptotic variances of the semiparametric estimates of Scott and Wild (1997, 2001) are compared to these bounds and the estimates are found to be fully efficient.