Coverage Error in Data Collection Combining Mobile Surveys With Passive Measurement Using Apps: Data From a German National Survey

Florian Keusch,Mark Trappmann,Sebastian Bähr,Frauke Kreuter,Georg-Christoph Haas

doi:10.1177/0049124120914924

Abstract

Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. In addition, different operating systems (OSs) limit how mobile data can be collected passively. These limitations cause concern about coverage error in studies targeting the general population. Based on data from the Panel Study Labour Market and Social Security (PASS), an annual probability-based mixed-mode survey on the labor market and poverty in Germany, we find that smartphone ownership and ownership of smartphones with specific OSs are correlated with a number of sociodemographic and substantive variables. The use of weighting techniques based on sociodemographic information available for both owners and nonowners reduces these differences but does not eliminate them.

Highlights

Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often
In accordance with the results of previous research on other European countries (Baier et al 2018; Fuchs and Busse 2009; Metzler and Fuchs 2014) and the United States (Couper et al 2018; Pew Research 2017), we find that smartphone owners are overrepresented among young and highly educated people and those who live in large communities
We find that smartphone ownership in Germany correlates with a number of substantive variables on the labor market and poverty, which are routinely collected as part of Panel Study Labour Market and Social Security (PASS)

Summary

Introduction

Researchers are combining self-reports from mobile surveys with passive data collection using sensors and apps on smartphones increasingly more often. While smartphones are commonly used in some groups of individuals, smartphone penetration is significantly lower in other groups. Different operating systems (OSs) limit how mobile data can be collected passively. These limitations cause concern about coverage error in studies targeting the general population. Based on data from the Panel Study Labour Market and Social Security (PASS), an annual probability-based mixed-mode survey on the labor market and poverty in Germany, we find that smartphone ownership and ownership of smartphones with specific OSs are correlated with a number of sociodemographic and substantive variables

Methods

Results

Conclusion