Identifiability of logistic regression with homoscedastic error: Berkson model

DOI10.15559/15-VMSTA27zbMath1349.62337arXiv1508.02841OpenAlexW3103371122MaRDI QIDQ340765

Sergiy Shklyar

Publication date: 15 November 2016

Published in: Modern Stochastics. Theory and Applications (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/1508.02841

zbMATH Keywords

logistic regressionerrors in variablesbinary regressionBerkson modelregression calibration model

Mathematics Subject Classification ID

Generalized linear models (logistic models) (62J12)

Cites Work

• The identification of logistic regression models with errors in the variables
• Logistic regression with homoscedastic errors—A Berkson model
• On Errors-in-Variables in Binary Regression-Berkson Case
• Measurement Error in Nonlinear Models

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