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Presented By: Michigan Program in Survey and Data Science

MPSDS JPSM Seminar Series - A Multivariate Stopping Rule for Survey Data Collection

Xinyu Zhang - Michigan Program in Survey and Data Science

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MPSDS JPSM Seminar Series
November 2, 2022
12:00 - 1:00 EDT

Xinyu Zhang
A Multivariate Stopping Rule for Survey Data Collection

Bio
Xinyu Zhang is a PhD candidate studying survey and data science at the University of Michigan. He is primarily interested in responsive survey designs, survey nonresponse, and machine learning techniques. His dissertation topic is using models to inform responsive survey designs.

Abstract
Surveys are experiencing declining response rates. With more and more effort expended to combat these declining response rates, the cost of large-scale surveys has continued to rise. Recent technological developments in survey data collection have allowed the survey designer to make near-real-time intervention decisions. Stopping rules are one of the interventions often considered to improve the efficiency of data collection. Stopping some cases essentially reallocates effort from stopped cases to others, but most previously proposed stopping rules have only considered single estimates. In multipurpose surveys, there may be data quality objectives that must be met for multiple estimates with constraints on costs. We introduce a stopping rule that accounts for the cost and the quality of one or more estimates. The proposed stopping rule is illustrated via simulation using data from the Health and Retirement Study.

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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