Advances in Decision Sciences
Volume 2007 (2007), Article ID 86180, 23 pages
doi:10.1155/2007/86180

On the semiparametric efficiency of the Scott-Wild estimator under choice-based and two-phase sampling

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.