September 2013
Intermediate to advanced
264 pages
5h
Chinese
Content preview from Bad Data 技術手冊
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第十章：偏頗與錯誤的微妙來源
其實是有一些策略能夠用來找出或甚至是解決其中一些偏頗，但為了怕沒有辦法能夠修
復偏頗的來源，知道這些問題可能會如何影響你的結果是很重要的。
超過上限∕超過下限
尾巴存在於任何的分佈中，而舉例來說，在工資或收入的狀況中，這些尾巴可能會很
長。為了要保護它的受訪者的資料，實施訪問的機構也許會使用單一值來將極高的值
（topcoding）或是極低的值（bottomcoding）置換掉。以 Current Population Survey
（CPS）當做例子，每個月由 U.S. Census Bureau 對超過 50,000 個家庭作訪問。在前幾
年， Census Bureau 會將超過上限的值以上限值替換。舉例來說，在 1996 年之前，工
資的上限設定為 $99,999，所以任何回報工資超過這個上限的人，他的工資值就會被置
換成 $99,999。這個程序的影響，就是會在該階層的工資分佈中產生一個突起。在最近
幾年， Census Bureau 會將超過一些（較高）門檻工資的值，使用類似特徵（特別是性
別、人種以及工作狀態）集合的人的平均工資來置換。
這個方法有兩個優點：第一，它不會在工資上限處產生單一的突起（儘管它會在上限之
上產生數個較小的突起）；第二，不論有沒有上限，所有工資的加總會是相同的。在最
近期的 CPS 中，在上限之上的工資在受訪者之間被交換；這保留了分佈的尾巴，但這樣
也改變了工資與其他性質之間的關聯（以保護受訪者）。
若沒有存取其他的資料來源（不論是行政資料或是將上下限移除之前的原始受訪資料） ...
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