A hybrid pairwise likelihood method
A hybrid pairwise likelihood method
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DOI：
10.1093/biomet/asm051
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发表时间：
2007-12-01
期刊：
影响因子：
2.7
通讯作者：
Kuk, Anthony Y. C.
中科院分区：
文献类型：
--
作者：
Kuk, Anthony Y. C.
提出了一种改进的两两似然方法，旨在提高边缘分布参数的估计。这是通过替换成对似然得分方程，估计这样的参数，由最佳的线性组合的边际得分函数。所提出的估计的边际参数的另一个优点，成对似然，是它是强大的错误指定的二元分布，只要正确指定的单变量边际分布。虽然交替逻辑回归可以被看作是所提出的方法的一个特殊情况下，它表明，现有的概括交替逻辑回归适用于有序数据是不一样的，是劣于所提出的方法，因为它取代了某些条件密度的伪密度，假设工作独立。拟合的多元负二项分布是另一种情况下，涉及棘手的可能性，要求使用成对的似然方法，并在模拟研究中证明了改进的方法的优越性。两个例子，根据蝾螈交配和病人自控镇痛数据的分析，证明了所提出的方法的实用性。最佳组合的成对，而不是边际，分数的可能性也被认为是其困难和潜力进行了讨论。
A modification to the pairwise likelihood method is proposed, which aims to improve the estimation of the marginal distribution parameters. This is achieved by replacing the pairwise likelihood score equations, for estimating such parameters, by the optimal linear combinations of the marginal score functions. A further advantage of the proposed estimator of marginal parameters, over pairwise likelihood, is that it is robust to misspecification of the bivariate distributions as long as the univariate marginal distributions are correctly specified. While alternating logistic regression can be seen as a special case of the proposed method, it is shown that an existing generalization of alternating logistic regression applicable to ordinal data is not the same as and is inferior to the proposed method because it replaces certain conditional densities by pseudodensities that assume working independence. The fitting of the multivariate negative binomial distribution is another scenario involving intractable likelihood that calls for the use of pairwise likelihood methods, and the superiority of the modified method is demonstrated in a simulation study. Two examples, based on the analyses of salamander mating and patient-controlled analgesia data, demonstrate the usefulness of the proposed method. The possibility of combining optimally the pairwise, rather than marginal, scores is also considered and its difficulty and potential are discussed.