國家衛生研究院 NHRI:Item 3990099045/5357
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    題名: Deletion diagnostics for generalized linear models using the adjusted Poisson likelihood function
    作者: Chien, LC;Tsou, TS
    貢獻者: Division of Biostatistics and Bioinformatics
    摘要: 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.
    日期: 2011-06
    關聯: 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
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