MPSDS and the JPSM Seminar Series: The Additional Effects of Adaptive Survey Design Beyond Post-Survey Adjustment: An Experimental Evaluation
Shiyu Zhang, Research Assistant and PhD Candidate, Michigan Program in Survey and Data Science
Wednesday, February 23
12pm to 1pm
Adaptive survey design refers to using targeted procedures to recruit different sampled cases. This technique strives to reduce bias and variance of survey estimates by trying to recruit a larger and more balanced set of respondents. However, it is not well understood how adaptive design can improve data and survey estimates beyond the well-established post-survey adjustment. This paper reports the results of an experiment that evaluated the additional effect of adaptive design to post-survey adjustments. The experiment was conducted in the Detroit Metro Area Communities Study in 2021. We evaluated the adaptive design in five outcomes: 1) response rates, 2) demographic composition of respondents, 3) bias and variance of key survey estimates, 4) changes in coefficients of regression model results, and 5) costs. The most significant benefit of the adaptive design was its ability to generate more efficient survey estimates with smaller variances and smaller design effects.