Accommodating covariates in receiver operating characteristic analysis Free xxx adult speed chat
Classification accuracy is the ability of a marker or diagnostic test to discriminate between two groups of individuals, cases and controls, and is commonly summarized using the receiver operating characteristic (ROC) curve.
In studies of classification accuracy, there are often covariates that should be incorporated into the ROC analysis.
[email protected] Janes, Fred Hutchinson Cancer Research Center and University of Washington, Seattle, WA.
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The PV for the case measure y_i is the standard normal cumulative distribution function of (y_i - mean)/sd, where the mean and the standard deviation (sd) are calculated by using the control sample. The correction is relevant only in calculating summary indices, such as the area under the ROC curve."oprobit" calculates PVs based on the fit of an ordered probit regression model of the marker on the adjustment covariates among controls."ologit" calculates PVs based on the fit of an ordered logit regression model of the marker on the adjustment covariates among controls. If TRUE, bootstrap samples are drawn from the combined sample (cohort sampling) rather than sampling separately from cases and controls (case-control sampling); default is FALSE (case-control sampling). If TRUE (default), bootstrap samples are drawn without respect to covariate strata.Alternatively, a single marker variable can be specified, in which case the requested ROC statistics are returned without comparison statistics.All ROC statistics are calculated by using PVs of the disease case measures relative to the corresponding marker distribution among controls (Pepe and Longton (2005), Huang and Pepe (in press)).