Hosseinian, SaharMorgenthaler, Stephan2011-12-162011-12-162011-12-16201110.1016/j.jspi.2010.11.015https://infoscience.epfl.ch/handle/20.500.14299/74394WOS:000286960500013Robust procedures increase the reliability of the results of a data analysis. We studied such a robust procedure for binary regression models based on the criterion of least absolute deviation. The resulting estimating equation consists in a simple modification of the familiar maximum likelihood equation. This estimator is easy to compute with existing computational procedures and gives a high degree of protection. (C) 2010 Elsevier B.V. All rights reserved.RobustnessGeneralized linear modelLogistic modelBounded influence functionMaximum likelihoodGeneralized Linear-ModelsLogistic-RegressionEstimatorFitstext::journal::journal article::research article