Evaluating mode effects in mixed-mode survey data using covariate adjustment models

Summary

The confounding of selection and measurement effects between different
modes is a disadvantage of mixed-mode surveys. Solutions to this problem
have been suggested in several studies. Most use adjusting covariates
to control selection effects. Unfortunately, these covariates must meet
strong assumptions, which are generally ignored. This article discusses
these assumptions in greater detail and also provides an alternative
model for solving the problem. This alternative uses adjusting
covariates, explaining measurement effects instead of selection effects.
The application of both models is illustrated by using data from a
survey on opinions about surveys, which yields mode effects in line with
expectations for the latter model, and mode effects contrary to
expectations for the former model. However, the validity of these
results depends entirely on the (ad hoc) covariates chosen. Research
into better covariates might thus be a topic for future studies.