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Series:   Elements in Quantitative and Computational Methods for the Social Sciences

Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias

Published online by Cambridge University Press:  29 September 2020

Devin Caughey ,
Adam J. Berinsky ,
Sara Chatfield ,
Erin Hartman ,
Eric Schickler  and
Jasjeet S. Sekhon
Devin Caughey
Affiliation:
Massachusetts Institute of Technology
Adam J. Berinsky
Affiliation:
Massachusetts Institute of Technology
Sara Chatfield
Affiliation:
University of Denver
Erin Hartman
Affiliation:
University of California, Los Angeles
Eric Schickler
Affiliation:
University of California, Berkeley
Jasjeet S. Sekhon
Affiliation:
University of California, Berkeley

Summary

We elaborate a general workflow of weighting-based survey inference, decomposing it into two main tasks. The first is the estimation of population targets from one or more sources of auxiliary information. The second is the construction of weights that calibrate the survey sample to the population targets. We emphasize that these tasks are predicated on models of the measurement, sampling, and nonresponse process whose assumptions cannot be fully tested. After describing this workflow in abstract terms, we then describe in detail how it can be applied to the analysis of historical and contemporary opinion polls. We also discuss extensions of the basic workflow, particularly inference for causal quantities and multilevel regression and poststratification.
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Keywords

weightingcalibrationecological inferencenonresponsequota sampling

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Type
Element
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Series: Elements in Quantitative and Computational Methods for the Social Sciences
Online ISBN: 9781108879217
Publisher: Cambridge University Press
Print publication: 22 October 2020

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