2021-04-122020-01-0122277390WOS;000567322300001SCOPUS;2-s2.0-85089678854http://hdl.handle.net/10784/27829Both cell-wise and case-wise outliers may appear in a real data set at the same time. Few methods have been developed in order to deal with both types of outliers when formulating a regression model. In this work, a robust estimator is proposed based on a three-step method named 3S-regression, which uses the comedian as a highly robust scatter estimate. An intensive simulation study is conducted in order to evaluate the performance of the proposed comedian 3S-regression estimator in the presence of cell-wise and case-wise outliers. In addition, a comparison of this estimator with recently developed robust methods is carried out. The proposed method is also extended to the model with continuous and dummy covariates. Finally, a real data set is analyzed for illustration in order to show potential applications. © 2020 by the authors.enghttps://v2.sherpa.ac.uk/id/publication/issn/2227-7390article3S-regressionCase-wise contaminationComedianMADMonte carlo simulationR softwareRobustnessRocke S-estimator2021-04-12Velasco H.Laniado H.Toro M.Leiva V.Lio Y.10.3390/MATH8081259