Matches in SemOpenAlex for { <https://semopenalex.org/work/W2166730394> ?p ?o ?g. }
Showing items 1 to 93 of
93
with 100 items per page.
- W2166730394 endingPage "991" @default.
- W2166730394 startingPage "980" @default.
- W2166730394 abstract "Election forecasts have traditionally been based on representative polls, in which randomly sampled individuals are asked who they intend to vote for. While representative polling has historically proven to be quite effective, it comes at considerable costs of time and money. Moreover, as response rates have declined over the past several decades, the statistical benefits of representative sampling have diminished. In this paper, we show that, with proper statistical adjustment, non-representative polls can be used to generate accurate election forecasts, and that this can often be achieved faster and at a lesser expense than traditional survey methods. We demonstrate this approach by creating forecasts from a novel and highly non-representative survey dataset: a series of daily voter intention polls for the 2012 presidential election conducted on the Xbox gaming platform. After adjusting the Xbox responses via multilevel regression and poststratification, we obtain estimates which are in line with the forecasts from leading poll analysts, which were based on aggregating hundreds of traditional polls conducted during the election cycle. We conclude by arguing that non-representative polling shows promise not only for election forecasting, but also for measuring public opinion on a broad range of social, economic and cultural issues." @default.
- W2166730394 created "2016-06-24" @default.
- W2166730394 creator A5027036879 @default.
- W2166730394 creator A5046597133 @default.
- W2166730394 creator A5054707908 @default.
- W2166730394 creator A5074093929 @default.
- W2166730394 date "2015-07-01" @default.
- W2166730394 modified "2023-10-13" @default.
- W2166730394 title "Forecasting elections with non-representative polls" @default.
- W2166730394 cites W1965609999 @default.
- W2166730394 cites W1975488571 @default.
- W2166730394 cites W2002868076 @default.
- W2166730394 cites W2014908010 @default.
- W2166730394 cites W2026649077 @default.
- W2166730394 cites W2105602542 @default.
- W2166730394 cites W2116942087 @default.
- W2166730394 cites W2136621417 @default.
- W2166730394 cites W2138030815 @default.
- W2166730394 cites W2142344524 @default.
- W2166730394 cites W2145067787 @default.
- W2166730394 cites W2150160077 @default.
- W2166730394 cites W2169025594 @default.
- W2166730394 cites W2289880760 @default.
- W2166730394 cites W2316477433 @default.
- W2166730394 cites W3124473222 @default.
- W2166730394 doi "https://doi.org/10.1016/j.ijforecast.2014.06.001" @default.
- W2166730394 hasPublicationYear "2015" @default.
- W2166730394 type Work @default.
- W2166730394 sameAs 2166730394 @default.
- W2166730394 citedByCount "239" @default.
- W2166730394 countsByYear W21667303942014 @default.
- W2166730394 countsByYear W21667303942015 @default.
- W2166730394 countsByYear W21667303942016 @default.
- W2166730394 countsByYear W21667303942017 @default.
- W2166730394 countsByYear W21667303942018 @default.
- W2166730394 countsByYear W21667303942019 @default.
- W2166730394 countsByYear W21667303942020 @default.
- W2166730394 countsByYear W21667303942021 @default.
- W2166730394 countsByYear W21667303942022 @default.
- W2166730394 countsByYear W21667303942023 @default.
- W2166730394 crossrefType "journal-article" @default.
- W2166730394 hasAuthorship W2166730394A5027036879 @default.
- W2166730394 hasAuthorship W2166730394A5046597133 @default.
- W2166730394 hasAuthorship W2166730394A5054707908 @default.
- W2166730394 hasAuthorship W2166730394A5074093929 @default.
- W2166730394 hasBestOaLocation W21667303941 @default.
- W2166730394 hasConcept C111919701 @default.
- W2166730394 hasConcept C134698397 @default.
- W2166730394 hasConcept C149782125 @default.
- W2166730394 hasConcept C162324750 @default.
- W2166730394 hasConcept C17744445 @default.
- W2166730394 hasConcept C197487636 @default.
- W2166730394 hasConcept C199539241 @default.
- W2166730394 hasConcept C204854418 @default.
- W2166730394 hasConcept C2776129789 @default.
- W2166730394 hasConcept C2779509655 @default.
- W2166730394 hasConcept C41008148 @default.
- W2166730394 hasConcept C94625758 @default.
- W2166730394 hasConceptScore W2166730394C111919701 @default.
- W2166730394 hasConceptScore W2166730394C134698397 @default.
- W2166730394 hasConceptScore W2166730394C149782125 @default.
- W2166730394 hasConceptScore W2166730394C162324750 @default.
- W2166730394 hasConceptScore W2166730394C17744445 @default.
- W2166730394 hasConceptScore W2166730394C197487636 @default.
- W2166730394 hasConceptScore W2166730394C199539241 @default.
- W2166730394 hasConceptScore W2166730394C204854418 @default.
- W2166730394 hasConceptScore W2166730394C2776129789 @default.
- W2166730394 hasConceptScore W2166730394C2779509655 @default.
- W2166730394 hasConceptScore W2166730394C41008148 @default.
- W2166730394 hasConceptScore W2166730394C94625758 @default.
- W2166730394 hasFunder F4320306076 @default.
- W2166730394 hasIssue "3" @default.
- W2166730394 hasLocation W21667303941 @default.
- W2166730394 hasLocation W21667303942 @default.
- W2166730394 hasOpenAccess W2166730394 @default.
- W2166730394 hasPrimaryLocation W21667303941 @default.
- W2166730394 hasRelatedWork W1964931383 @default.
- W2166730394 hasRelatedWork W1982588320 @default.
- W2166730394 hasRelatedWork W2030741299 @default.
- W2166730394 hasRelatedWork W2066633175 @default.
- W2166730394 hasRelatedWork W2084722888 @default.
- W2166730394 hasRelatedWork W2113473815 @default.
- W2166730394 hasRelatedWork W2123046331 @default.
- W2166730394 hasRelatedWork W2151491083 @default.
- W2166730394 hasRelatedWork W2635649669 @default.
- W2166730394 hasRelatedWork W3046546205 @default.
- W2166730394 hasVolume "31" @default.
- W2166730394 isParatext "false" @default.
- W2166730394 isRetracted "false" @default.
- W2166730394 magId "2166730394" @default.
- W2166730394 workType "article" @default.