IASS Webinar 27: Designed big data in surveys and official statistics: Augmenting surveys with sensors, apps, wearables and data donation

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Date/Time
Date(s) - 29/03/2023
2:00 pm - 3:30 pm

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IASS Webinar 27: Designed big data in surveys and official statistics: Augmenting surveys with sensors, apps, wearables and data donation

Speaker: Bella Struminskaya

Tuesday, March 29th 2:00 – 3:30 CET

Please register for the IASS Webinar at: https://bit.ly/IASS-webinar-27

After registering, you will receive a confirmation email containing information about joining the webinar. There will be time for questions. The webinar will be recorded and made available on the IASS and ISI web site. See below for the abstract and biography of the speakers.

Abstract:

Traditional surveys are not well-equipped to measure certain concepts of interest such as expenditures, time use or travel behavior due to high burden placed on participants. Facts or behaviors that are difficult to measure through self-report can be measured using new technologies: smartphone apps, sensors, and wearables. For example, accelerometers in smartphones and fitness bracelets can objectively measure physical activity, screen time apps can measure (social) media use. Another possibility is to augment surveys with administrative data or data from digital platforms such as Google, Youtube, Instagram that participants can provide to researchers through data donation, or consent to data linkage. However, to ensure representation, participants have to be willing and able to use their devices to perform such tasks. If participants differ from nonparticipants in key outcomes, research results can be biased. In this webinar, I will present the results of several randomized experiments on the mechanisms of willingness and consent to collect data using smartphone sensors, apps, and wearables in general population surveys, and the extent of nonparticipation bias assessed by linkage of survey data to sensor and administrative data. I will further focus on how these mechanisms translate to data donation of digital trace data, what opportunities and challenges such novel data collection methods hold for the social sciences and official statistics, and outline future research agenda.

Bio:

Bella Struminskaya is an Assistant Professor of Methodology and Statistics at Utrecht University and an affiliated researcher at Statistics Netherlands. Her research focuses on the design and implementation of online, mixed-mode and smartphone surveys, and passive data collection. She has published on augmenting surveys with mobile apps and sensors, data quality, nonresponse and measurement error, including panel conditioning, and device effects.