Bounding mean regressions when a binary regressor is mismeasured
type: Item
instance of: scholarly article
title: Bounding mean regressions when a binary regressor is mismeasured
zbMATH Open document ID: 0861.62079
DOI: 10.1016/S0304-4076(95)01730-5
author: Christopher R. Bollinger
published in: Journal of Econometrics
publication date: 1997-04-28T00:00:00Z
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 62J05
Mathematics Subject Classification ID: 62J99
zbMATH DE Number: 955403
zbMATH Keywords: measurement error
zbMATH Keywords: binary variables
zbMATH Keywords: consistency
zbMATH Keywords: asymptotic normality
zbMATH Keywords: identification
zbMATH Keywords: mean regression models
zbMATH Keywords: binary regressor
zbMATH Keywords: probability of misclassification
MaRDI profile type: Publication
cites work: Regression with a binary independent variable subject to errors of observation
cites work: Restricting Regression Slopes in the Errors-in-Variables Model by Bounding the Error Correlation
cites work: Q4759305
cites work: Consistent Sets of Estimates for Regressions with Errors in All Variables
cites work: Bounding the effects of measurement error in regressions involving dichotomous variables
cites work: Bounding the Effects of Proxy Variables on Regression Coefficients
full work available at URL: s0304-4076(95)01730-5
OpenAlex ID: W2148021834
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description: scientific article; zbMATH DE number 955403