國家衛生研究院 NHRI:Item 3990099045/5357
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    Please use this identifier to cite or link to this item: http://ir.nhri.org.tw/handle/3990099045/5357


    Title: Deletion diagnostics for generalized linear models using the adjusted Poisson likelihood function
    Authors: Chien, LC;Tsou, TS
    Contributors: Division of Biostatistics and Bioinformatics
    Abstract: In this article, we propose two novel diagnostic measures for the deletion of influential observations for regression parameters in the setting of generalized linear models. The proposed diagnostic methods are capable for detecting the influential observations under model misspecification, as long as the true underlying distributions have finite second moments. More specifically, it is demonstrated that the Poisson likelihood function can be properly adjusted to become asymptotically valid for practically all underlying discrete distributions. The adjusted Poisson regression model that achieves the robustness property is presented. Simulation studies and an illustration are performed to demonstrate the efficacy of the two novel diagnostic procedures.
    Date: 2011-06
    Relation: Journal of Statistical Planning and Inference. 2011 Jun;141(6):2044-2054.
    Link to: http://dx.doi.org/10.1016/j.jspi.2010.12.016
    JIF/Ranking 2023: http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcAuth=NHRI&SrcApp=NHRI_IR&KeyISSN=0378-3758&DestApp=IC2JCR
    Cited Times(WOS): https://www.webofscience.com/wos/woscc/full-record/WOS:000288308900005
    Cited Times(Scopus): http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=79651475420
    Appears in Collections:[Others] Periodical Articles

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