Estimating mode effects from a sequential mixed-mode experiment using structural moment models

Until recently, the survey mode of the household panel studyUn-derstanding Societywas mainly face-to-face interview but it has nowadopted a mixed-mode design where individuals can selfcomplete thequestionnaire via the web. As mode is known to affect survey data,a randomized mixed-mode experiment was implemented during thefirst year of the two-year Wave 8 fieldwork period to assess the im-pact of this change. The experiment involved a sequential design thatpermits the identification of mode effects in the presence of nonig-norable nonrandom mode selection. While previous studies have usedinstrumental variables regression to estimate the effects of mode onthe means of the survey variables, we set up a more general framework based on novel structural moment models to characterize the effect of mode on the distribution of the survey variables by its effect on the moments of the joint distribution. We adapt our estimation procedure to account for nonresponse and complex sampling designs, and to include suitable auxiliary data to improve inferences and relax key assumptions. Finally, we demonstrate how to estimate the effects of mode on the parameter estimates from generalized linear and other exponential family models when both outcomes and predictors are subject to mode effects. This framework is used to investigate the impact of the move to web mode on Wave 8 of Understanding Society.