Tree-based model checking for logistic regression.
A tree procedure is proposed to check the adequacy of a fitted logistic regression model. The proposed method not only makes natural assessment for the logistic model, but also provides clues to amend its lack-of-fit. The resulting tree-augmented logistic model facilitates a refined model with meaningful interpretation. We demonstrate its use via simulation studies and an application to the Pima Indians diabetes data.
Su
Xiaogang
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Department of Statistics and Actuarial Science, University of Central Florida, Orlando, FL 32816, USA. xiaosu@mail.ucf.edu
D035843:Biomedical Research / Q000706:statistics & numerical data*; D003627:Data Interpretation, Statistical; D003920:Diabetes Mellitus; D006801:Humans; D007198:Indians, North American; D016015:Logistic Models; D014481:United States