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dc.contributor.author陳昱均en_US
dc.contributor.authorChen, Yu-Chunen_US
dc.contributor.author陳鄰安en_US
dc.contributor.authorChen, Lin-Anen_US
dc.date.accessioned2014-12-12T02:40:32Z-
dc.date.available2014-12-12T02:40:32Z-
dc.date.issued2013en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#GT070152605en_US
dc.identifier.urihttp://hdl.handle.net/11536/74425-
dc.description.abstract我們觀察到,傳統中介變項的分析中的直接影響力和中介質有關,而我們認為的直接影響力是不經由中介質所產生 的。而後,我們提出了一個新的中介變相分析,此分析中的影響力可分解出直接影響與間接影響,其中新的直接影響是 不透過中介值的。我們新的假設檢定力相較於傳統 Baron 和 Kenny 的假設檢定力是有明顯改善。最後我們將中介變項的 分析和交互作用做聯結。zh_TW
dc.description.abstractWe observe that the classical mediation analysis gives the direct effect involving the inputs of mediated variable leading that the direct effect and indirect effect do not serve their roles appropriately. We then propose a new mediation analysis with interaction identification for determining a clean direct effect for defining the total effect and then the effect decomposition. Power comparison between the Baron and Kenny’ s test and a new test based on our approach for indirect effect detection has been done and their corresponding efficiencies for detection are displayed. A new indirect effect proportion then is proposed for further investigation.en_US
dc.language.isoen_USen_US
dc.subject中介變項zh_TW
dc.subject中介值zh_TW
dc.subject分解效應zh_TW
dc.subject交互作用zh_TW
dc.subjectMediationen_US
dc.subjectMediatoren_US
dc.subjectEffect Decompositionen_US
dc.subjectInteractionen_US
dc.title中介變項統計分析zh_TW
dc.titleStatistical Mediation Analysisen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
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