An Alternative Approach to Multivariate Response Error Models for Sample Survey Data with Applications to Estimators Involving Subclass Means

Abstract

Indicator functions are used as the basis for the formulation of a multivariate extension of the response error model developed by the U.S. Bureau of the Census. This approach allows a more complete characterization for general survey designs of the nature of the various components of the total variance of linear sample estimators and is particularly useful with respect to the role of the interaction component. These results are then applied to study the effect of response errors on subclass means, differences between subclass means, and post-stratified means.