title: Using a mixture model to predict the occurrence of diabetic retinopathy.
abstract: Diabetes mellitus is a common condition which has several serious complications associated with it. In this paper a mixture model, based on one previously used to predict the onset of AIDS, is used to predict the onset of one of these complications, diabetic retinopathy, the major cause of adult blindness in the U.K. This model differs from the previous AIDS model by introducing covariates into the model and using a wider choice of mixture distributions. The fit and distributional assumptions of the model are then discussed for this example. The model is fitted to the data by maximum likelihood. It is important that the training set contains balanced numbers of individuals with and without retinopathy.
authors: Department of Applied Statistics, University of Reading, U.K.
authors: P
authors: P
authors: Young
authors: B
authors: B
authors: Morgan
authors: P
authors: P
authors: Sonksen
authors: S
authors: S
authors: Till
authors: C
authors: C
authors: Williams
mesh_terms: D000163:Acquired Immunodeficiency Syndrome / Q000453:epidemiology / Q000209:etiology; D000704:Analysis of Variance; D003627:Data Interpretation, Statistical; D003930:Diabetic Retinopathy / Q000453:epidemiology* / Q000209:etiology; D006801:Humans; D016013:Likelihood Functions; D008432:Mathematical Computing; D015233:Models, Statistical; D011336:Probability; D012306:Risk