Journal of the Korean Statistical Society

The Korean Statistical Society (한국통계학회)
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EXTENSION OF FACTORING LIKELIHOOD APPROACH TO NON-MONOTONE MISSING DATA

  • Kim, Jae-Kwang (Department of Applied Statistics, Yonsei University)
  • Published : 2004.12.01
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Abstract

We address the problem of parameter estimation in multivariate distributions under ignorable non-monotone missing data. The factoring likelihood method for monotone missing data, termed by Rubin (1974), is extended to a more general case of non-monotone missing data. The proposed method is algebraically equivalent to the Newton-Raphson method for the observed likelihood, but avoids the burden of computing the first and the second partial derivatives of the observed likelihood. Instead, the maximum likelihood estimates and their information matrices for each partition of the data set are computed separately and combined naturally using the generalized least squares method.

Keywords

References

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