{"title":"投票率的空间自相关","authors":"Mahdi-Salim Saib","doi":"10.4172/2155-6180.1000376","DOIUrl":null,"url":null,"abstract":"The presence of spatial autocorrelation in the data can yield biased or inconsistent point estimates when Ordinary Least Squares (OLS) model is used inappropriately. Therefore, in this paper we try to assess the fit of the model taking into account the autocorrelation in analyze of voting behavior in the 2007 French Presidential Elections and the 2010 French Regional Elections. We find that the voter turnout in the Il de France region is spatially structured and that the Simultaneous Auto-Regressive (SAR) model clearly improves the quality of adjustment compared with the OLS model for the both elections.","PeriodicalId":87294,"journal":{"name":"Journal of biometrics & biostatistics","volume":"8 1","pages":"1-4"},"PeriodicalIF":0.0000,"publicationDate":"2017-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Spatial Autocorrelation in Voting Turnout\",\"authors\":\"Mahdi-Salim Saib\",\"doi\":\"10.4172/2155-6180.1000376\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The presence of spatial autocorrelation in the data can yield biased or inconsistent point estimates when Ordinary Least Squares (OLS) model is used inappropriately. Therefore, in this paper we try to assess the fit of the model taking into account the autocorrelation in analyze of voting behavior in the 2007 French Presidential Elections and the 2010 French Regional Elections. We find that the voter turnout in the Il de France region is spatially structured and that the Simultaneous Auto-Regressive (SAR) model clearly improves the quality of adjustment compared with the OLS model for the both elections.\",\"PeriodicalId\":87294,\"journal\":{\"name\":\"Journal of biometrics & biostatistics\",\"volume\":\"8 1\",\"pages\":\"1-4\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2017-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of biometrics & biostatistics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4172/2155-6180.1000376\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of biometrics & biostatistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4172/2155-6180.1000376","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The presence of spatial autocorrelation in the data can yield biased or inconsistent point estimates when Ordinary Least Squares (OLS) model is used inappropriately. Therefore, in this paper we try to assess the fit of the model taking into account the autocorrelation in analyze of voting behavior in the 2007 French Presidential Elections and the 2010 French Regional Elections. We find that the voter turnout in the Il de France region is spatially structured and that the Simultaneous Auto-Regressive (SAR) model clearly improves the quality of adjustment compared with the OLS model for the both elections.
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