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Local influence for incomplete data models

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  • Hong‐Tu Zhu
  • Sik‐Yum Lee

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.

Suggested Citation

  • Hong‐Tu Zhu & Sik‐Yum Lee, 2001. "Local influence for incomplete data models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 63(1), pages 111-126.
    • Handle: RePEc:bla:jorssb:v:63:y:2001:i:1:p:111-126
    DOI: 10.1111/1467-9868.00279
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