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Journal paper
篇名(中)以多重插補法重建政黨支持比率的圖像:以2008總統大選前夕面訪案資料為例
篇名(英)Reconstruct Partisan Support Distribution with Multiply Imputed Survey Data: A Case Study of Taiwan's 2008 Presidential Election
論文屬性研究論文
作者姓名(中)劉正山
作者姓名(英)Frank C.S. Liu
頁碼135-162
Abstract透過調查樣本來推估得票率是選舉預測方式之中非常使用的方 法。然而,即使抽樣過程恰當且具有自體代表性,受訪者在面對投票 給誰這類問題時所產生的拒答現象卻往往造成資料的遺失,進而造成 點估計的偏誤。這個情形在選舉期間的投票意願調查或敏感問題的謂 聳格外嚴重。這個嚴重遺漏值的問題不但導致民眾對於使用調查資料 的預測能力失去信心,也造成學者對於這些資料產生出來的描述統計 數據感到懷疑。本研究嘗試以多重插補法進行遺失資料(missing data) 補足的工作,並將此法應用到政黨得票率的點估計上。本研究 使用台灣2008 年總統選舉前蒐集的「台灣選舉與民主化調查」面訪資 料(Taiwan's Election and Democratization Study for the 2008 legislative elections, TEDS2008L, N=1,240) ,比較多重插補前後與 雨黨候選人支持率的差異。研究發現,使用多重插補法將有助於修正 因高度遺漏值所造成的候選人支持率的點估計偏誤。
摘要(英)Analyzing survey data is one of the most promising methods by which to predict election results. But respondents may conceal their preferences. Hence, it has been difficult for researchers to obtain true partisan support distributions of with one survey data set. Given the constraints of cost, could we possibly predict vote shares more accurately with one sample? This paper employs multiple imputation (MI) for point estimation as a way to (re)construct the distribution of partisan supporters in Taiwan's 2008 presidential election. The findings show an identifiable difference between the biased point estimation and a better one of using MI. Althoùgh there remain other types of errors that may influence the accuracy of a prediction, readers may find this method rela tively cost efficient when formulating strategies to improve point estimation pertaining to election results.
Keyword多重插補法;政黨傾向;調查研究;點估計;選舉預測
關鍵字(英)multiple imputation; partisanship; survey research; missing values; election prediction
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