一类有序列联表的基于logit变换和对称分解的扩展不对称模型

IF 0.6 Q4 STATISTICS & PROBABILITY

Electronic Journal of Applied Statistical Analysis Pub Date : 2021-05-20 DOI:10.1285/I20705948V14N1P1

Kengo Fujisawa, Jin Kinoshita, Kouji Tahata

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引用次数: 0

摘要

对称(或不对称)的问题在分析方形列联表时自然出现。许多现有的不对称模型没有对主对角线单元的约束。因此，主对角线单元格上的观测值对似然比卡方检验统计量没有贡献。在此，我们提出了一个模型，表明对数赔率的不对称性。它可以利用主对角线单元格中的信息。同时，将对称模型分解为若干模型，包括本文提出的模型。

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Extended asymmetry model based on logit transformation and decomposition of symmetry for square contingency tables with ordered categories

The issues of symmetry (or asymmetry) arises naturally for the analysis of square contingency tables. Many existing asymmetry models do not have the constraints on the main diagonal cells. Thus, the observations on the main diagonal cells do not contribute to the likelihood ratio chi-squared test statistics. Herein we propose a model that indicates the asymmetry for the log odds.It can utilize the information in the main diagonal cells. Also, the symmetry model is separated into some models including the proposed model.

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来源期刊

Electronic Journal of Applied Statistical Analysis STATISTICS & PROBABILITY-

CiteScore

1.40

自引率

14.30%

发文量