Estimation in Multiple-Frame Surveys

Abstract

Multiple-frame surveys are commonly used to decrease costs of sampling or to reduce undercoverage that could occur if only one sampling frame were used. We describe potential uses and examples of multiple-frame surveys. We then derive optimal linear estimators and pseudo–maximum likelihood estimators for the population total when samples are taken independently from each frame using probability sampling designs. We explore the properties of these estimators theoretically and through a simulation study. We also derive variance estimators and discuss some practical problems that may be encountered in multiple-frame surveys.