2010年10月

以多重挿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
Reconstruct Partisan Support Distribution with Multiply Imputed Survey Data: A Case Study of Taiwan's 2008 Presidential Election

研究論文 Article

劉正山
Frank C.S. Liu

135-162

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母體代表性，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調查格外嚴重。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。本研究嘗試以多重挿補法進行遺失資料（missingData）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），比較多重挿補前後與兩黨候選人支持率的差異。研究發現，使用多重挿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。

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.

多重挿補法, 政黨傾向, 調查研究, 點估計, 選舉預測
multiple imputation, partisanship, survey research, missing values, election prediction

政治學, 社會學
Political Science, Sociology

https://doi.org/10.7014/SRMA.2010100004

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