MPSDS JPSM Seminar Series
March 15, 2023
12:00 - 1:00 EST

The Zoom call will be locked 10 minutes after the start of the presentation.

Annette Jäckle is Professor of Survey Methodology at the Institute for Social and Economic Research at the University of Essex, UK and Associate Director of Innovations and Co-Investigator of the UK Household Longitudinal Study: Understanding Society. Her research interests are in methodology of data collection for longitudinal studies, mixed mode data collection, questionnaire design, respondent consent to data linkage, and new ways of using mobile devices for survey data collection.

Abstract
Data linkage usually requires informed consent of respondents, whether for legal or ethical reasons. A common problem is that when consent questions are asked in self-completion surveys, respondents are much less likely to consent than when they are asked for consent in interviewer administered surveys. In the existing literature, predictors of consent are mostly inconsistent, between studies, but also between different consents asked within one study. In addition, experiments with the wording of consent questions have often had no or inconsistent effects. Why is this? And what can be done to increase informed consent to data linkage? This presentation provides an overview of what we have learnt from qualitative in-depth interviews and a series of experiments implemented in two UK probability household panels (the Understanding Society Innovation Panel and COVID-19 study) and in the UK PopulusLive online access panel. We address the following questions. (1) How do respondents decide whether to consent to data linkage? (2) Why are respondents less likely to consent in web than CAPI surveys? (3) How best to ask for multiple consents within a survey? (4) Which wording and formats affect informed consent and why? We end the overview with a summary of the practical implications for how best to ask for consent to data linkage.

Michigan Program in Survey and Data Science (MPSDS)
The University of Michigan Program in Survey Methodology was established in 2001 seeking to train future generations of survey and data scientists. In 2021, we changed our name to the Michigan Program in Survey and Data Science. Our curriculum is concerned with a broad set of data sources including survey data, but also including social media posts, sensor data, and administrative records, as well as analytic methods for working with these new data sources. And we bring to data science a focus on data quality — which is not at the center of traditional data science. The new name speaks to what we teach and work on at the intersection of social research and data. The program offers doctorate and master of science degrees and a certificate through the University of Michigan. The program's home is the Institute for Social Research, the world's largest academically-based social science research institute.

Summer Institute in Survey Research Techniques (SISRT)
The mission of the Summer Institute is to provide rigorous and high quality graduate training in all phases of survey research. The program teaches state-of-the-art practice and theory in the design, implementation, and analysis of surveys. The Summer Institute in Survey Research Techniques has presented courses on the sample survey since the summer of 1948, and has offered such courses every summer since. Graduate-level courses through the Program in Survey and Data Science are offered from June 5 through July 28 and available to enroll in as a Summer Scholar.

The Summer Institute uses the sample survey as the basic instrument for the scientific measurement of human activity. It presents sample survey methods in courses designed to meet the educational needs of those specializing in social and behavioral research such as professionals in business, public health, natural resources, law, medicine, nursing, social work, and many other domains of study.