title: Practical investigation of the performance of robust logistic regression to predict the genetic risk of hypertension.
abstract: Logistic regression is usually applied to investigate the association between inherited genetic variants and a binary disease phenotype. A limitation of standard methods used to estimate the parameters of logistic regression models is their strong dependence on a few observations deviating from the majority of the data. We used data from the Genetic Analysis Workshop 18 to explore the possible benefit of robust logistic regression to estimate the genetic risk of hypertension. The comparison between standard and robust methods relied on the influence of departing hypertension profiles (outliers) on the estimated odds ratios, areas under the receiver operating characteristic curves, and clinical net benefit. Our results confirmed that single outliers may substantially affect the estimated genotype relative risks. The ranking of variants by probability values was different in standard and in robust logistic regression. For cutoff probabilities between 0.2 and 0.6, the clinical net benefit estimated by leave-one-out cross-validation in the investigated sample was slightly larger under robust regression, but the overall area under the receiver operating characteristic curve was larger for standard logistic regression. The potential advantage of robust statistics in the context of genetic association studies should be investigated in future analyses based on real and simulated data.
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 305, 69120 Heidelberg, Germany ; Clinical Epidemiology, Integrated Research and Treatment Center, Center for Sepsis Control and Care (CSCC), Jena University Hospital, Erlanger Allee 101, 07747 Jena, Germany.
authors.forename: Miriam
authors.initials: M
authors.lastname: Kesselmeier
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 305, 69120 Heidelberg, Germany.
authors.forename: Carine
authors.initials: C
authors.lastname: Legrand
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 305, 69120 Heidelberg, Germany.
authors.forename: Barbara
authors.initials: B
authors.lastname: Peil
authors.affiliation: Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DFKZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
authors.forename: Maria
authors.initials: M
authors.lastname: Kabisch
authors.affiliation: Institute of Human Genetics, University Hospital Heidelberg, Im Neuenheimer Feld 366, 69120 Heidelberg, Germany.
authors.forename: Christine
authors.initials: C
authors.lastname: Fischer
authors.affiliation: Molecular Genetics of Breast Cancer, Deutsches Krebsforschungszentrum (DFKZ), Im Neuenheimer Feld 580, 69120 Heidelberg, Germany.
authors.forename: Ute
authors.initials: U
authors.lastname: Hamann
authors.affiliation: Institute of Medical Biometry and Informatics, University of Heidelberg, Im Neuenheimer Feld 305, 69120 Heidelberg, Germany.
authors.forename: Justo
authors.initials: J
authors.lastname: Lorenzo Bermejo