Publikation: Contributions to Understanding - Pre-Election Poll Accuracy: A Cross-Election Perspective
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Pre-election polls play a crucial role in informing researchers, pollsters, candidates, and the public, serving as a significant empirical application of statistical principles. However, it has become increasingly apparent over recent decades that these polls do not consistently align with actual election results. Understanding the factors contributing to the success or failure of polls poses a considerable challenge. This dissertation seeks to enhance our comprehension of pre-election poll accuracy through a cross-election perspective. Using diverse data sources, recent political science advancements, and hierarchical Bayesian modeling techniques, I systematically explore numerous potential correlates of poll accuracy at the respondent-, poll-, and election-level. In collaboration with my colleagues, I employ and refine hierarchical Bayesian modeling techniques and elaborate theories on correlates of polling errors within the Total Survey Error (TSE) framework.
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CHEN, Sina, 2024. Contributions to Understanding - Pre-Election Poll Accuracy: A Cross-Election Perspective [Dissertation]. Konstanz: Universität KonstanzBibTex
@phdthesis{Chen2024-02-23Contr-70412, year={2024}, title={Contributions to Understanding - Pre-Election Poll Accuracy: A Cross-Election Perspective}, author={Chen, Sina}, address={Konstanz}, school={Universität Konstanz} }
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