An important problem associated with two-sample surveys is the estimation of nonlinear functions of finite population totals such as ratios, correlation coefficients or measures of income inequality. Computation and estimation of the variance of such complex statistics are made more difficult by...

Fekri and Ruiz-Gazen [2004. Robust weighted orthogonal regression in the errors-in-variables model. J. Multivar. Anal. 88, 89-108] propose a new class of robust estimators in the errors-in-variables linear model (EIV model) under the assumption that the measurement error variances are equal. In...

This paper focuses on robust estimation in the structural errors-in-variables (EV) model. A new class of robust estimators, called weighted orthogonal regression estimators, is introduced. Robust estimators of the parameters of the EV model are simply derived from robust estimators of...

We argue that the conditional bias associated with a sample unit can be a useful measure of influence in finite population sampling. We use the conditional bias to derive robust estimators that are obtained by downweighting the most influential sample units. Under the model-based approach to...