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Voting patterns in 2016: Exploration using multilevel regression and poststratification (MRP) on pre-election polls

Rob Trangucci, Imad Ali, Andrew Gelman, Doug Rivers

arXiv 2 Feb 2018 · Statistics — Applications · 8 citations (OpenAlex)

arXiv:1802.00842 · PDF · DOI · OpenAlex · Extracted main text

Abstract

We analyzed 2012 and 2016 YouGov pre-election polls in order to understand how different population groups voted in the 2012 and 2016 elections. We broke the data down by demographics and state. We display our findings with a series of graphs and maps. The R code associated with this project is available at https://github.com/rtrangucci/mrp_2016_election/.

Citation extraction

5
references
9
in-text mentions
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distinct cited
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self-citations
6,634
main-text words

appendix boundary found by appendix_titled_section at “Appendix A - Model Code” · 98% of the source is main text. Read the extracted text to check this.

Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1Yair Ghitza and Andrew Gelman (2013) Deep interactions with MRP: Election turnout and voting patterns among small electoral subgroups self0.73732100%
2Rayleigh Lei, Andrew Gelman, and Yair Ghitza (2017) The 2008 election: A preregistered replication analysis self0.51121100%
3Andrew Gelman and Thomas C Little (1997) Poststratification into many categories using hierarchical logistic regression self0.40511100%
4Sarah Flood, Miriam King, Steven Ruggles, and J. Robert Warren (2017) Integrated public use microdata series, current population survey: Version 5.0. [dataset], 20170.40511100%
5Stan Development Team (2016) RStanArm: Bayesian applied regression modeling via Stan. R package version 2.13.1., 20160.40511100%
*unmatched citation key *0.000110%

Showing the top 6 of 6 scored citations. 1 of these could not be matched to a bibliography entry, so only the citation key is shown.