title: Local influence to detect influential data structures for generalized linear mixed models.
abstract: This article discusses the generalization of the local influence measures for normally distributed responses to local influence measures for generalized linear models with random effects. For these models, it is shown that the subject-oriented influence measure is a special case of the proposed observation-oriented influence measure. A two-step diagnostic procedure is proposed. The first step is to search for influential subjects. A search for influential observations is proposed as the second step. An illustration of a two-treatment, multiple-period crossover trial demonstrates the practical importance of the detection of influential observations in addition to the detection of influential subjects.
authors.affiliation: Department of Methodology and Statistics, Maastricht University, The Netherlands. mario.ouwens@stat.unimaas.nl
authors.forename: M J
authors.initials: MJ
authors.lastname: Ouwens
authors.forename: F E
authors.initials: FE
authors.lastname: Tan
authors.forename: M P
authors.initials: MP
authors.lastname: Berger
mesh_terms: D001218:Aspartame / Q000009:adverse effects; D001699:Biometry; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data; D018592:Cross-Over Studies; D006261:Headache / Q000139:chemically induced; D006801:Humans; D016014:Linear Models
chemical_list: D001218:Aspartame