Hot adult dating free member dating - Accommodating covariates in roc analysis

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One of them is a formal redundancy analysis where each predictor is nonlinearly predicted from all the other predictors, in turn. Variable clustering, principal component analysis, and factor analysis are other possibilities.

We usually adjust for other risk factors like gender or age when devising such cut-off (using ROC curve analysis).

Now, what about adjusting impulsivity (IMP) on gender, age, and sensation seeking (SS) since SS is known to correlate with IMP?

In this paper we propose a dependent Bayesian nonparametric model for conditional ROC estimation.

Our model is based on dependent Dirichlet processes, where the covariate-dependent ROC curves are indirectly modeled using probability models for related probability distributions in the diseased and healthy groups.

The proposed model is applied to data concerning diagnosis of diabetes.

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