title: A regression shrinkage method tailored to qualitative regressors and clustered data.
abstract: We propose a shrinkage method for estimation in linear regression models with qualitative regressors. Due to the nature of the shrinkage constraint, this method tends to give estimates that are exactly zero for some groups of coefficients belonging to the same regressor. The method hence results in concise models, since some of the regressors are entirely eliminated. In conjunction with this estimation method, a model with a fixed cluster effect turns out to be closely related to frailty models. We apply the method for modelling hospital readmissions.
authors.affiliation: Assistance Publique-Hôpitaux de Paris (AP-HP), 3, Avenue Victoria, F-75184 Paris Cedex 04, France.
authors.forename: Anke
authors.initials: A
authors.lastname: Neumann
authors.forename: Josiane
authors.initials: J
authors.lastname: Holstein
authors.forename: Gilles
authors.initials: G
authors.lastname: Chatellier
authors.forename: Eric
authors.initials: E
authors.lastname: Lepage
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D001499:Bayes Theorem; D002648:Child; D002675:Child, Preschool; D016000:Cluster Analysis; D005260:Female; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010359:Patient Readmission; D012044:Regression Analysis