Target Estimation and Adjustment Weighting for Survey Nonresponse and Sampling Bias

Elaborates a general workflow of weighting-based survey inference and how it can be applied to the analysis of opinion polls.

Devin Caughey (Author), Adam J. Berinsky (Author), Sara Chatfield (Author), Erin Hartman (Author), Eric Schickler (Author), Jasjeet S. Sekhon (Author)

9781108794152, Cambridge University Press

Paperback / softback, published 22 October 2020

75 pages
15 x 23 x 0.6 cm, 0.16 kg

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.

1. The Problem of Unrepresentative Survey Samples
2. Weight Estimation
3. Target Estimation
4. Application to Contemporary Election Surveys
5. Application to Quota-sampled Opinion Polls
6. Extensions and Conclusion.

Subject Areas: Probability & statistics [PBT], Social research & statistics [JHBC], Society & social sciences [J]