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Presented By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series - Would electoral research show different findings if we replaced probability face-to-face surveys with other types of surveys?

Hannah Bucher - University of Mannheim, Leibniz-Institute for the Social Sciences, German Longitudinal Election Study

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MPSDS JPSM Seminar Series
October 26, 2022
12:00 - 1:00 pm

Would electoral research show different findings if we replaced probability face-to-face surveys with nonprobability online surveys?

Hannah Bucher is a PhD student in survey research at the University of Mannheim and a research associate at GESIS - Leibniz-Institute for the Social Sciences at the German Longitudinal Election Study (GLES). Her research focuses on (non)probability online surveys.

As respondents of nonprobability online surveys are self-selected, it is often questioned whether results are comparable with those of probability face-to-face surveys. In this paper, I compare a nonprobability online survey and a probability face-to-face survey by the German Longitudinal Election Study (GLES) in terms of estimation of benchmark statistics; distributions in 80 variables covering measures of political attitudes and behavior; and differences in results of multivariate analyses through a multimodel comparison with individual-level voter turnout as the dependent variable. The probability face-to-face survey performs slightly better in estimating characteristics with external benchmarks. There are substantial differences in numerous variables and their associations in multivariate models. Thus, switching from a probability face-to-face survey to a nonprobability online survey affects empirical findings on individual-level voter turnout and the conclusions drawn therefrom.

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.

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.
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