Local influence for incomplete data models |
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Authors: | Hong-Tu Zhu & Sik-Yum Lee |
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Institution: | University of Victoria, Canada,;Chinese University of Hong Kong, People's Republic of China |
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Abstract: | This paper proposes a method to assess the local influence in a minor perturbation of a statistical model with incomplete data. The idea is to utilize Cook's approach to the conditional expectation of the complete-data log-likelihood function in the EM algorithm. It is shown that the method proposed produces analytic results that are very similar to those obtained from a classical local influence approach based on the observed data likelihood function and has the potential to assess a variety of complicated models that cannot be handled by existing methods. An application to the generalized linear mixed model is investigated. Some illustrative artificial and real examples are presented. |
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Keywords: | EM algorithm Generalized linear mixed model Local influence Model perturbation Normal curvature |
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