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Goodness-of-Fit Tests for the Ordinal Response Models with Misspecified Links

  • 발행 : 2009.07.31

초록

The Pearson chi-squared statistic or the deviance statistic is widely used in assessing the goodness-of-fit of the generalized linear models. But these statistics are not proper in the situation of continuous explanatory variables which results in the sparseness of cell frequencies. We propose a goodness-of-fit test statistic for the cumulative logit models with ordinal responses. We consider the grouping of a dataset based on the ordinal scores obtained by fitting the assumed model. We propose the Pearson chi-squared type test statistic, which is obtained from the cross-classified table formed by the subgroups of ordinal scores and the response categories. Because the limiting distribution of the chi-squared type statistic is intractable we suggest the parametric bootstrap testing procedure to approximate the distribution of the proposed test statistic.

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참고문헌

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피인용 문헌

  1. Latent class analysis with multiple latent group variables vol.24, pp.2, 2017, https://doi.org/10.5351/CSAM.2017.24.2.173
  2. Notes on the Goodness-of-Fit Tests for the Ordinal Response Model vol.23, pp.6, 2010, https://doi.org/10.5351/KJAS.2010.23.6.1057