title: Dirichlet negative multinomial regression for overdispersed correlated count data.
abstract: A generic random effects formulation for the Dirichlet negative multinomial distribution is developed together with a convenient regression parameterization. A simulation study indicates that, even when somewhat misspecified, regression models based on the Dirichlet negative multinomial distribution have smaller median absolute error than generalized estimating equations, with a particularly pronounced improvement when correlation between observations in a cluster is high. Estimation of explanatory variable effects and sources of variation is illustrated for a study of clinical trial recruitment.
authors.affiliation: Cochrane Institute of Primary Care and Public Health, Cardiff University, Neuadd Meirionnydd, Heath Park, Cardiff CF14 4YS, UK. farewelld@cf.ac.uk
authors.forename: Daniel M
authors.initials: DM
authors.lastname: Farewell
authors.forename: Vernon T
authors.initials: VT
authors.lastname: Farewell
mesh_terms: D056808:Biostatistics; D002986:Clinical Trials as Topic / Q000706:statistics & numerical data*; D003198:Computer Simulation; D003627:Data Interpretation, Statistical; D006801:Humans; D016014:Linear Models; D008137:Longitudinal Studies; D015233:Models, Statistical; D018579:Patient Selection; D012044:Regression Analysis