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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/72219


    Title: Goodness of fit tests with misclassified data
    Authors: Hsueh,Huey-Miin;Cheng, K. F.;Chieh, T. H.
    薛慧敏
    Contributors: 統計系
    Date: 1998
    Issue Date: 2014-12-23 15:09:18 (UTC+8)
    Abstract: The most popular goodness of fit test for a multinomial distribution is the chi-square test. But this test is generally biased if observations are subject to misclassification, In this paper we shall discuss how to define a new test procedure when we have double sample data obtained from the true and fallible devices. An adjusted chi-square test based on the imputation method and the likelihood ratio test are considered, Asymptotically, these two procedures are equivalent. However, an example and simulation results show that the former procedure is not only computationally simpler but also more powerful under finite sample situations.
    Relation: Communications in Statistics - Theory and Methods,27(6),1379-1393
    Data Type: article
    Appears in Collections:[Department of Statistics] Periodical Articles

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