Bounding the effects of measurement error in regressions involving dichotomous variables

DOI10.1016/0304-4076(88)90010-3zbMath0667.62051OpenAlexW1996584880MaRDI QIDQ1117646

Steven Klepper

Publication date: 1988

Published in: Journal of Econometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/0304-4076(88)90010-3

zbMATH Keywords

multiple regressionerrors-in-variables modeldichotomous independent variableseffects of measurement errorleast-squares regression coefficient estimators

Mathematics Subject Classification ID

Applications of statistics to economics (62P20) Linear regression; mixed models (62J05)

Related Items (7)

Bounding parameters in a linear regression model with a mismeasured regressor using additional information ⋮ Partial identification of probability distributions with misclassified data ⋮ Bayesian moment-based inference in a regression model with misclassification error ⋮ Bounding mean regressions when a binary regressor is mismeasured ⋮ Binary misclassification and identification in regression models ⋮ A note on the closed-form identification of regression models with a mismeasured binary regressor ⋮ Regressor diagnostics for the classical errors-in-variables model

Cites Work

• Regressor diagnostics for the classical errors-in-variables model
• Maximum likelihood estimation of the polychoric correlation coefficient
• Regression with a binary independent variable subject to errors of observation
• Consistent Sets of Estimates for Regressions with Errors in All Variables
• Identification in the Linear Errors in Variables Model
• Comment on Identification in the Linear Errors in Variables Model
• Extending the Classical Normal Errors-in-Variables Model

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