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广义线性模型族的广义霍斯默-莱梅肖拟合优度检验。

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

作者信息

Surjanovic Nikola, Lockhart Richard A, Loughin Thomas M

机构信息

Department of Statistics, University of British Columbia, Vancouver, BC Canada.

Department of Statistics and Actuarial Science, Simon Fraser University, Burnaby, BC Canada.

出版信息

Test (Madr). 2024;33(2):589-608. doi: 10.1007/s11749-023-00912-8. Epub 2023 Dec 19.

Abstract

UNLABELLED

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.

SUPPLEMENTARY INFORMATION

The online version contains supplementary material available at 10.1007/s11749-023-00912-8.

摘要

未标注

广义线性模型(GLMs)应用非常广泛,但针对模型整体拟合度的正式拟合优度(GOF)检验似乎仅在某些类型的GLMs中广泛使用。我们开发并应用了一种新的拟合优度检验,类似于著名且常用的霍斯默 - 莱梅肖(HL)检验,它可用于多种GLMs。检验统计量是HL统计量的一种变体,但我们使用施图特和朱(《斯堪的纳维亚统计杂志》29(3):535 - 545, 2002)的方法严格推导了渐近正确的抽样分布,并证明了其一致性。我们将新检验的性能与GLMs的其他GOF检验进行了比较,包括将HL检验直接简单应用于泊松问题的情况。在各种模拟设置中,我们的检验提供了具有竞争力或相当的功效,并且我们确定了一种情况,即该检验的简单版本无法保持其检验水平。我们的广义HL检验易于实施和解释,并且有一个R包可供公开获取。

补充信息

在线版本包含可在10.1007/s11749 - 023 - 00912 - 8获取的补充材料。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/b742/11164741/c7932c575ca8/11749_2023_912_Fig1_HTML.jpg

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