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題名 選舉民調與選戰動態分析---貝式統計模型的應用
其他題名 Analyzing Election Polls and Campaign Dynamics--- A Bayesian Modeling Approach
作者 俞振華
貢獻者 行政院國家科學委員會
國立政治大學選舉研究中心
關鍵詞 選舉民調；機構效應；系統性偏誤；資料合併；時間序列
Bayesian Statistical Modeling; Election polls; House effects; Systematic
     biases; Pooling data; Time series
日期 2010
上傳時間 5-Dec-2012 11:07:26 (UTC+8)
摘要 本研究以 2008 年總統大選前近三個月內各媒體所發佈的民調數據為基礎，利用貝式統計模型分析時間序列，以評估媒體民調包括TVBS/年代、中國時報、遠見、聯合報、及蘋果日報等的機構效應—即是否媒體民調結果有所謂偏藍偏綠的傾向。實証研究發現，並非每個媒體機構所發佈的民調結果都有所謂「機構效應」存在。此外，透過時間序列模型及Kalman Filtering and Smoothing Algorithm的應用，本研究整合了過去的選舉結果、實際的選舉結果、及即時的民調資料來描繪馬英九的兩黨支持度在競選期間每日的變化。
This analysis uses Bayesian modeling approach to assess time series of media’s poll data and to explore the so-called “house effect”. Specifically, we collected data three months prior to the 2008 Presidential Election from five media institutions—namely, TVBS/ERA, China Times, Global Vision Monthly, United Daily News, and Apple Daily to analyze whether their poll results biased toward Pan-blue or Pan-green camps. Our findings are twofold: first, while some media poll results have a consistent “house effect”, some do not have such systematic bias. Second, by utilizing Kalman Filtering and Smoothing Algorithm and combining past and recent election results as well as updated poll numbers, this analysis successfully depict day-to-day changes of Ma ying-jeou’s two-party vote during the campaign period.
關聯 基礎研究
學術補助
研究期間:9901~ 9907
研究經費:218仟元
資料類型 report
dc.contributor 行政院國家科學委員會en_US
dc.contributor 國立政治大學選舉研究中心en_US
dc.creator (作者) 俞振華zh_TW
dc.date (日期) 2010en_US
dc.date.accessioned 5-Dec-2012 11:07:26 (UTC+8)-
dc.date.available 5-Dec-2012 11:07:26 (UTC+8)-
dc.date.issued (上傳時間) 5-Dec-2012 11:07:26 (UTC+8)-
dc.identifier.uri (URI) http://nccur.lib.nccu.edu.tw/handle/140.119/56389-
dc.description.abstract (摘要) 本研究以 2008 年總統大選前近三個月內各媒體所發佈的民調數據為基礎，利用貝式統計模型分析時間序列，以評估媒體民調包括TVBS/年代、中國時報、遠見、聯合報、及蘋果日報等的機構效應—即是否媒體民調結果有所謂偏藍偏綠的傾向。實証研究發現，並非每個媒體機構所發佈的民調結果都有所謂「機構效應」存在。此外，透過時間序列模型及Kalman Filtering and Smoothing Algorithm的應用，本研究整合了過去的選舉結果、實際的選舉結果、及即時的民調資料來描繪馬英九的兩黨支持度在競選期間每日的變化。-
dc.description.abstract (摘要) This analysis uses Bayesian modeling approach to assess time series of media’s poll data and to explore the so-called “house effect”. Specifically, we collected data three months prior to the 2008 Presidential Election from five media institutions—namely, TVBS/ERA, China Times, Global Vision Monthly, United Daily News, and Apple Daily to analyze whether their poll results biased toward Pan-blue or Pan-green camps. Our findings are twofold: first, while some media poll results have a consistent “house effect”, some do not have such systematic bias. Second, by utilizing Kalman Filtering and Smoothing Algorithm and combining past and recent election results as well as updated poll numbers, this analysis successfully depict day-to-day changes of Ma ying-jeou’s two-party vote during the campaign period.-
dc.language.iso en_US-
dc.relation (關聯) 基礎研究en_US
dc.relation (關聯) 學術補助en_US
dc.relation (關聯) 研究期間:9901~ 9907en_US
dc.relation (關聯) 研究經費:218仟元en_US
dc.subject (關鍵詞) 選舉民調；機構效應；系統性偏誤；資料合併；時間序列en_US
dc.subject (關鍵詞) Bayesian Statistical Modeling; Election polls; House effects; Systematic
     biases; Pooling data; Time series		-
dc.title (題名) 選舉民調與選戰動態分析---貝式統計模型的應用zh_TW
dc.title.alternative (其他題名) Analyzing Election Polls and Campaign Dynamics--- A Bayesian Modeling Approachen_US
dc.type (資料類型) reporten