A Mean Squared Error Model for Dual Frame, Mixed Mode Survey Design

An error model for dual frame survey designs is developed. It includes components of error for sampling variance, interviewer variance, and bias in each frame. A cost model that attempts to capture the complexity of a full scale dual frame survey is presented. The error and cost models are applied to a large national survey, the National Crime Survey, and the effect that alternative levels of bias in both frames have on the optimal allocation of sample to the two frames is examined for two types of crime.