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    Title: 多層線性模型的分層樣本數組合問題:對跨國政治文化研究的啟示
    Authors: 呂宜勵
    Contributors: 黃旻華
    呂宜勵
    Keywords: 多層線性模型
    一般化貝氏模型
    反覆抽樣
    抽樣設計
    Date: 2006
    Issue Date: 2009-09-19 15:29:00 (UTC+8)
    Abstract: 政治學者近年來已將多層線性模型當作研究政治文化的重要工具,不但應用在既有的資料庫分析上,同時也希望在資料蒐集過程中將所需要的資料特性納入抽樣設計裏,以期能克服目前此法在應用上所面臨的問題。在眾多問題中,最重要的莫過於是「總樣本數一定下個體和總體層次樣本數組合如何影響推論可靠性的問題」,學界對此過往是採取「30/30原則」,也就是個體和總體層次的樣本數都至少要在30個以上推論才會比較穩定,但近來許多研究顯示,如果將個體層次的樣本數縮減到15個而極大化總體層次樣本數,所得出的推論會比「30/30原則」來得更穩定,因此許多學者紛紛倡議應採用新發現而捨棄「30/30原則」。本文針對這樣的提議,利用教育學及政治學二領域資料,從模型意含的討論,進而使用模擬方法來測試這樣的提議是否站得住腳。

    本文發現「極大化總體層次樣本數」原則並不能當作普遍認知,因為過往的所有文獻皆對單一母體資料進行剖析,尚未察覺母體資料型態影響參數表現的可能性,然而,本研究變化不同資料特性進行模擬結果顯示,母體資料結構確實會造成不同的參數表現,以致最適樣本組合也跟著不同。另外,我們觀察到固定效果和隨機效果的最適樣本配置偏重於不同層次的樣本數目,固定參數、固定效果以總體層次為主,但隨機參數、隨機效果、迴歸參數等卻不能忽視個體層次樣本個數,所以研究者都應該認真思考其在意的參數為何,才能針對所關切的現象本身設計出最適樣本配置,而做出實質且有效的討論。
    Reference: 一. 中文部份
    黃紀
    2005 「多層抽樣設計芻議」,發表於「台灣選舉與民主化調查研究方工作坊」學術研討會(TEDS Workshop),民國94年3月26、27日,台北:政治大學綜合院館三樓演講廳。
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    Description: 碩士
    國立政治大學
    政治研究所
    93252005
    95
    Source URI: http://thesis.lib.nccu.edu.tw/record/#G0093252005
    Data Type: thesis
    Appears in Collections:[政治學系] 學位論文

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