The 2020 Election In The United States: Beta Regression Versus Regression Quantiles

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985807%3A_____%2F21%3A00553129" target="_blank" >RIV/67985807:_____/21:00553129 - isvavai.cz</a>

Výsledek na webu

<a href="https://relik.vse.cz/2021/download/pdf/380-Kalina-Jan-paper.pdf" target="_blank" >https://relik.vse.cz/2021/download/pdf/380-Kalina-Jan-paper.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

The 2020 Election In The United States: Beta Regression Versus Regression Quantiles

Popis výsledku v původním jazyce

The results of the presidential election in the United States in 2020 desire a detailed statistical analysis by advanced statistical tools, as they were much different from the majority of available prognoses as well as from the presented opinion polls. We perform regression modeling for explaining the election results by means of three demographic predictors for individual 50 states: weekly attendance at religious services, percentage of Afroamerican population, and population density. We compare the performance of beta regression with linear regression, while beta regression performs only slightly better in terms of predicting the response. Because the United States population is very heterogeneous and the regression models are heteroscedastic, we focus on regression quantiles in the linear regression model. Particularly, we develop an original quintile regression map, such graphical visualization allows to perform an interesting interpretation of the effect of the demographic predictors on the election outcome on the level of individual states.

Název v anglickém jazyce

The 2020 Election In The United States: Beta Regression Versus Regression Quantiles

Popis výsledku anglicky

The results of the presidential election in the United States in 2020 desire a detailed statistical analysis by advanced statistical tools, as they were much different from the majority of available prognoses as well as from the presented opinion polls. We perform regression modeling for explaining the election results by means of three demographic predictors for individual 50 states: weekly attendance at religious services, percentage of Afroamerican population, and population density. We compare the performance of beta regression with linear regression, while beta regression performs only slightly better in terms of predicting the response. Because the United States population is very heterogeneous and the regression models are heteroscedastic, we focus on regression quantiles in the linear regression model. Particularly, we develop an original quintile regression map, such graphical visualization allows to perform an interesting interpretation of the effect of the demographic predictors on the election outcome on the level of individual states.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

50601 - Political science

Projekt

—

Návaznosti

I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

RELIK 2021. Conference Proceedings

ISBN

978-80-245-2429-0

ISSN

—

e-ISSN

—

Počet stran výsledku

11

Strana od-do

321-331

Název nakladatele

Prague University of Economics and Business

Místo vydání

Prague

Místo konání akce

Praha

Datum konání akce

4. 11. 2021

Typ akce podle státní příslušnosti

EUR - Evropská akce

Kód UT WoS článku

—