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Activity Number: 492
Type: Contributed
Date/Time: Wednesday, August 3, 2016 : 8:30 AM to 10:20 AM
Sponsor: Survey Research Methods Section
Abstract #321430 View Presentation
Title: Predicting and Preventing Break-Offs in Web Surveys
Author(s): Felicitas Mittereder*
Companies: University of Michigan
Keywords: Nonresponse ; Administrative Data ; Adaptive Design ; Web Survey ; Break-Off ; Prediction

Due to the shift in survey data collection from mail to web surveys, breaking off prior to the end of a survey becomes a more prevalent problem on web. Given the lower response rate in web surveys, it is crucial to keep as many and as diverse respondents as we possibly can to maintain a high data quality standard and thus accurate survey estimates. As a first step of preventing and reducing break-offs, this study aims to predict the exact break-off timing in an online German labor force survey, which was conducted by the Institute for Employment Research (IAB), Research Institute of the Federal Employment Agency, Nuernberg, Germany. This study will make use of the survey data, along with the rich paradata and accessible administrative information from the sampling frame to investigate the factors that associated with breakoffs using logit modeling and survival analyses approach.

Authors who are presenting talks have a * after their name.

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