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Errors-in-variables unit gamma regression models
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DOI：10.1080/00949655.2025.2595530.png)
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Abstract
En 中文
The main goal of this paper is to propose a unit gamma regression model accounting for measurement errors in covariates. Additionally, we evaluate parameter estimation methods via Monte Carlo simulations and develop diagnostic tools including residuals and local influence measures to identify influential observations and assess model adequacy. We then apply this framework to model the waist-to-height ratio, a key anthropometric index for risk of cardiometabolic disorders.
Keywords:
Errors-in-variables
approximate maximum likelihood
unit gamma distribution
residual analysis
local influence
Journal
J
IF:
1.2
Papers:
131
Citations:
4.1K