Pantazis, Lucio JoséGarcía, Rafael Antonio2023-12-072023-12-072022-10-24https://ri.itba.edu.ar/handle/123456789/4229Detection of atypical response trajectories in biomedical longitudinal databasesMany health care professionals and institutions manage longitudinal databases, involving follow-ups for different patients over time. Longitudinal data frequently manifest additional complexities such as high variability, correlated measurements and missing data. Mixed effects models have been widely used to overcome these difficulties. This work proposes the use of linear mixed effects models as a tool that allows to search conceptually different types of anomalies in the data simultaneously.enLONGITUDINAL DATAMIXED EFFECTS MODELSOUTLIER DETECTIONDATA LONGITUDINALMODELO DE EFECTOS MIXTOSArtículo de Publicación Periódicahttps://doi.org/10.1515/ijb-2020-0076