A generalized Hosmer–Lemeshow goodness-of-fit test for a family of generalized linear models

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Abstract

Generalized linear models (GLMs) are very widely used, but formal goodness-of-fit (GOF) tests for the overall fit of the model seem to be in wide use only for certain classes of GLMs. We develop and apply a new goodness-of-fit test, similar to the well-known and commonly used Hosmer–Lemeshow (HL) test, that can be used with a wide variety of GLMs. The test statistic is a variant of the HL statistic, but we rigorously derive an asymptotically correct sampling distribution using methods of Stute and Zhu (Scand J Stat 29(3):535–545, 2002) and demonstrate its consistency. We compare the performance of our new test with other GOF tests for GLMs, including a naive direct application of the HL test to the Poisson problem. Our test provides competitive or comparable power in various simulation settings and we identify a situation where a naive version of the test fails to hold its size. Our generalized HL test is straightforward to implement and interpret and an R package is publicly available.

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Surjanovic, N., Lockhart, R. A., & Loughin, T. M. (2024). A generalized Hosmer–Lemeshow goodness-of-fit test for a family of generalized linear models. Test, 33(2), 589–608. https://doi.org/10.1007/s11749-023-00912-8

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