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Robust Probit Model

The Robust Probit Model estimates the probability of a binary outcome using the probit link function while protecting inference from misspecification of the error distribution or heteroscedasticity. Coefficients are obtained via maximum likelihood; standard errors are then replaced by the sandwich (Huber-White) estimator, which remains consistent even when the assumed error variance is incorrect.

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Robust Probit Regression Model

Taksonomisk metoderegister · regression-model / statistics

Wooldridge, J. M. (2010). Econometric Analysis of Cross Section and Panel Data (2nd ed.). MIT Press. · ISBN 978-0262232586
White, H. (1982). Maximum Likelihood Estimation of Misspecified Models. Econometrica, 50(1), 1–25. · DOI 10.2307/1912526

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Taxonomic bucketGeneralized Linear Modelmachine-suggested · Relational suggestion, not evidence.See alsoLogistic Regressionmachine-suggested · Relational suggestion, not evidence.Same method familyRobust Logistic Regressionmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketRobust Regressionmachine-suggested · Relational suggestion, not evidence.