Correcting survey measurement error with big data from road sensors through capture-recapture

Cover dissertation Klinwort 2020 Correcting survey measurement error with big data from road sensors through capture-recapture
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Using capture-recapture to correcy survey measurement error with big data from road sensors.
This thesis developed a method to estimate the underreporting based on an application of capture-recapture techniques. Six different estimators are applied. More specifically, a post-stratified survey estimator, a naive extension of the survey estimator, two conditional likelihood capture-recapture estimators, and two unconditional likelihood capture-recapture estimators are applied, compared, and discussed. The capture-recapture estimators correct for both nonresponse and measurement errors. The survey estimate is corrected for selective nonresponse. Therefore, a potential difference between capture-recapture and survey point estimates can be attributed to measurement error. The violation of the capture-recapture assumption of homogeneous capture probabilities is corrected by modeling heterogeneity in capture probabilities using logistic regression and log-linear models. The effects of occasional violations of the perfect linkage assumption are evaluated within sensitivity analyses. The flexibility, as well as the limitations of the applied estimators, are evaluated in a stratified capture-recapture analysis.

A specific use of big data in official statistics to estimate underreporting bias is demonstrated. However, this method is not limited to official statistics but can also be used in other disciplines, such as social sciences. The method presented applies to any validation study, where survey, administrative, and sensor data (or any other external big data source) can be linked on a micro-level using a unique identifier. This research is a new example of multi-source statistics, a promising approach to improve the benefits of sensor data in the field of official statistics.

Klingwort, J. (2020). Correcting survey measurement error with big data from road sensors through capture-recapture. Dissertation, University of Duisburg-Essen, doi:10.17185/duepublico/72081.