Modified chi-squared tests improve goodness-of-fit assessment in generalized linear models, highlighting their applicability.
Generalized linear models are applied for data analysis in various areas. One of the most important steps in fitting the model is to check the goodness-of-fit; however, there is a lack of such tests. Modified chi-squared goodness-of-fit tests for generalized linear models were constructed. Models with continuous right-skewed, possibly censored responses were considered. Explicit formulas of test statistics are provided in the case of gamma and inverse Gaussian models. The test power was investigated by simulation. The article presents real data examples to illustrate the application of tests.
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Bagdonavičius et al. (2025) studied this question.
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