Incompatibility of Model Specifications in Generalized Linear Models

The choice of regression models can vary depending on a study’s objectives and the characteristics of the dataset. Yet it is crucial to recognize that the properties of conditional expectation impose a natural consistency requirement on the formulation of these models. This paper endeavors to demons...

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Bibliographic Details
Published in:Biometrical letters 2024-06, Vol.61 (1), p.33-50
Main Authors: Feng, Changyong, Wang, Hongyue, Liu, Honghong
Format: Article
Language:English
Subjects:
conditional expectation
linear regression
logistic regression
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Summary:The choice of regression models can vary depending on a study’s objectives and the characteristics of the dataset. Yet it is crucial to recognize that the properties of conditional expectation impose a natural consistency requirement on the formulation of these models. This paper endeavors to demonstrate that, even under the most favorable assumptions concerning the covariates’ structure, inconsistent specifications can arise in generalized linear models, particularly when nonlinear link functions are employed.
ISSN:2199-577X
1896-3811
2199-577X
DOI:10.2478/bile-2024-0003