Accommodating covariates in receiver operating characteristic analysis
"linear" fits a linear regression of the marker distribution on the adjustment covariates among controls.
Standardized residuals based on this fitted linear model are used in place of the marker values for cases and controls.
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.
"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.
[email protected] Janes, Fred Hutchinson Cancer Research Center and University of Washington, Seattle, WA.
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Estimate and compare ROC summary statistics between two markers.
Choices for summary statistics are: ROC(f), the True positive rate corresponding to False positive rate f; ROC^(-1)(t), the False positive rate corresponding to True positive rate t; AUC, the area under the ROC curve; and p AUC(f), the partial area under the ROC curve from 0 to f.
Search for accommodating covariates in receiver operating characteristic analysis:
List containing properties for requested summary statistics, where Aasthaa Bansal, University of Washington, Seattle, WA.