title: A mixed-effects multinomial logistic regression model.
abstract: A mixed-effects multinomial logistic regression model is described for analysis of clustered or longitudinal nominal or ordinal response data. The model is parameterized to allow flexibility in the choice of contrasts used to represent comparisons across the response categories. Estimation is achieved using a maximum marginal likelihood (MML) solution that uses quadrature to numerically integrate over the distribution of random effects. An analysis of a psychiatric data set, in which homeless adults with serious mental illness are repeatedly classified in terms of their living arrangement, is used to illustrate features of the model.
authors.affiliation: Division of Epidemiology & Biostatistics, School of Public Health, University of Illinois at Chicago, Chicago, IL 60612, USA. hedeker@uic.edu
authors.forename: Donald
authors.initials: D
authors.lastname: Hedeker
mesh_terms: D000328:Adult; D002140:California; D016000:Cluster Analysis; D006703:Ill-Housed Persons; D006798:Housing; D006801:Humans; D016013:Likelihood Functions; D016015:Logistic Models; D008137:Longitudinal Studies; D028642:Persons with Psychiatric Disorders; D011632:Public Assistance; D012946:Social Welfare