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Using a mixture model to predict the occurrence of diabetic retinopathy
Author(s) -
Young Philip,
Morgan Byron,
Sonksen Peter,
Till Sebastian,
Williams Charles
Publication year - 1995
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.4780142308
Subject(s) - diabetic retinopathy , computer science , econometrics , statistics , diabetes mellitus , medicine , mathematics , endocrinology
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.