Abstract
The simple logistic regression model with normal measurement error and normal regressor is shown to be identifiable without any extra information about the measurement error. The multiple logistic regression model with more than one regressor variable measured with error is not identifiable. If the covariance matrix of the measurement error is known up to a scalar factor, the model is identified. Further we discuss why in spite of the identifiability the models cannot be estimated in a reasonable way without extra information about the measurement error.
Similar content being viewed by others
References
R.J. Carroll, C.H. Spiegelman, K.K.G. Lan, K.T. Bailey, and R.D. Abbott. On errors in variables in binary regression models.Biometrika, 71:19–26, 1984.
H. Küchenhoff.Logit- und Probitregression mit Fehlern in den Variablen. Volume 117 ofMathematical Systems in Economics. Verl. A. Hain, Frankfurt am Main, 1989.
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Küchenhoff, H. The identification of logistic regression models with errors in the variables. Stat Papers 36, 41–47 (1995). https://doi.org/10.1007/BF02926017
Received:
Revised:
Published:
Issue Date:
DOI: https://doi.org/10.1007/BF02926017