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OverviewWe 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. Full Product DetailsAuthor: Devin Caughey (Massachusetts Institute of Technology) , Adam J. Berinsky (Massachusetts Institute of Technology) , Sara Chatfield (University of Denver) , Erin Hartman (University of California, Los Angeles)Publisher: Cambridge University Press Imprint: Cambridge University Press Dimensions: Width: 23.00cm , Height: 0.60cm , Length: 15.00cm Weight: 0.160kg ISBN: 9781108794152ISBN 10: 1108794157 Pages: 75 Publication Date: 22 October 2020 Audience: General/trade , General Format: Paperback Publisher's Status: Active Availability: Manufactured on demand ![]() We will order this item for you from a manufactured on demand supplier. Table of Contents1. 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.ReviewsAuthor InformationTab Content 6Author Website:Countries AvailableAll regions |