A goodness of fit test for sparse 2p contingency tables
A goodness of fit test for sparse 2p contingency tables
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DOI：
10.1348/000711002159617
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发表时间：
2002-05-01
影响因子：
2.6
通讯作者：
Leung, SO
中科院分区：
文献类型：
--
作者：
Bartholomew, DJ;Leung, SO
当模型适合 20 个列联表中的数据时，许多单元格的预期频率可能非常小。这种稀疏性使得拟合优度的卡方或对数似然检验的分布的通常近似无效。我们通过基于表二阶边缘的观察频率和预期频率的比较提出测试来提出这个问题的解决方案。使用渐近矩提供采样分布的 X 2 近似。这可以根据预期的小区频率直接计算出来。新的测试适用于之前发布的几个与潜变量模型拟合相关的示例，但其应用相当普遍。
When a model is fitted to data in a 20 contingency table many cells are likely to have very small expected frequencies. This sparseness invalidates the usual approximation to the distribution of the chi-squared or log-likelihood tests of goodness of fit. We present a solution to this problem by proposing a test based on a comparison of the observed and expected frequencies of the second-order margins of the table. A X 2 approximation to the sampling distribution is provided using asymptotic moments. This can be straightforwardly calculated from the expected cell frequencies. The new test is applied to several previously published examples relating to the fitting of latent variable models, but its application is quite general.