Název: The 2022 Election in the United States: Reliability of a Linear Regression Model
Autoři: Kalina, Jan ; Vidnerová, Petra ; Večeř, M.
Typ dokumentu: Příspěvky z konference
Konference/Akce: RELIK 2023: Reproduction of Human Capital - mutual links and connections /16./, Praha (CZ), 20231123
Rok: 2023
Jazyk: eng
Abstrakt: In this paper, the 2022 United States election to the House of Representatives is analyzed by means of a linear regression model. After the election process is explained, the popular vote is modeled as a response of 8 predictors (demographic characteristics) on the state-wide level. The main focus is paid to verifying the reliability of two obtained regression models, namely the full model with all predictors and the most relevant submodel found by hypothesis testing (with 4 relevant predictors). Individual topics related to assessing reliability that are used in this study include confidence intervals for predictions, multicollinearity, and also outlier detection. While the predictions in the submodel that includes only relevant predictors are very similar to those in the full model, it turns out that the submodel has better reliability properties compared to the full model, especially in terms of narrower confidence intervals for the values of the popular vote.
Klíčová slova: elections results; electoral demography; linear regression; reliability; variability
Číslo projektu: GA21-19311S (CEP)
Poskytovatel projektu: GA ČR
Zdrojový dokument: RELIK 2023. Conference Proceedings, ISBN 978-80-245-2499-3

Instituce: Ústav informatiky AV ČR (web)
Informace o dostupnosti dokumentu: Dokument je dostupný na externích webových stránkách.
Externí umístění souboru: https://relik.vse.cz/2023/download/pdf/689-Vidnerova-Petra-paper.pdf
Původní záznam: https://hdl.handle.net/11104/0349891

Trvalý odkaz NUŠL: http://www.nusl.cz/ntk/nusl-538555


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