American Statistical Association
New York City
Metropolitan Area Chapter

Levin Lecture Series: Fall 2019 Colloquium Seminars
Department of Biostatistics
Mailman School of Public Health
Columbia University



DESIGNING COMBINED DATA PRODUCTS:
EXAMPLES FROM ECONOMIC RESEARCH STUDIES

by

Dr. Frauke Kreuter
Professor and Director in Joint Program in Survey Methodology
University of Maryland

Host: Qixuan Chen


Abstract

Combining data from different sources will be key for social scientists to take full advantage of the data deluge resulting from the increasing digitalization of society. Currently we see many attempts at using single (big data sources) with mixed results, the most exciting projects rely on a combination of different data, some still collected with traditional modes. This talk will highlight a few approaches and provide a framework with which researchers can think about creating new data products. An important element in this endeavor is however the respect of people's privacy. While different cultures have different norms about the collection on specific types of data for specific purposes, the notion of contextual integrity still holds. Learning how to design data collections for new insights in a more holistic way, will be the overarching theme of this talk.

In the talk I will be using several Economic Research examples, in particular the IAB-SMART research project to discuss privacy issues and the approaches to create high quality combined data sources. See the attached paper for details on the privacy part. In brief: The IAB-SMART study combines data from administrative records, surveys, and digital traces from smart phones. The digital trace data are collected via an app. The purpose of the IAB- SMART study is to measure the effects of long-term unemployment on social integration and social activity, as well as the inhibiting effects of reduced social networks and activities in finding reentry into the labor market. To create measures of social integration access to the phone's address book and usage is required, as well as sensory data from accelerometer and geoposition. For valid population estimates statisticians need to account for potential coverage bias and bias due to nonresponse and measurement error. Using the case study I will demonstrate how we approached these problems.


Date: Monday, October 21, 2019
Time: 11:30 A.M. - 12:30 P.M.
Location: Mailman School of Public Health
Department of Biostatistics
722 West 168th Street
Hammer Building
Room LL106
New York, New York

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