podc.est: Partial ODC Estimation

In tpAUC: Estimation and Inference of Two-Way pAUC, pAUC and pODC

Description

Estimate the area of region under ordinal dominance curve with pre-specific FNR constraint (FNR-pODC). See Yang et al., 2017 for details.

Usage

podc.est(response, predictor, threshold = 0.9, method = "MW",
  smooth = FALSE)

Arguments

response	a factor, numeric or character vector of responses; typically encoded with 0 (negative) and 1 (positive). Only two classes can be used in a ROC curve. If its levels are not 0 and 1, the first level will be defaultly regarded as negative.
predictor	a numeric vector of the same length than response, containing the predicted value of each observation. An ordered factor is coerced to a numeric.
threshold	numeric; false negative rate (FNR) constraint.
method	methods to estimate partial ODC. MW: Mann-Whitney statistic. expect: method in Yang et al., 2017 adapted from Wang and Chang, 2011. jackknife: jackknife method in Yang et al., 2017.
smooth	if TRUE, the ODC curve is passed to smooth to be smoothed.

Details

This function estimates FNR partial ODC given response, predictor and pre-specific FNR constraint. MW: Mann-Whitney statistic. expect: method in Yang et al., 2017 adapted from Wang and Chang, 2011. jackknife: jackknife method in Yang et al., 2017.

Value

Estimation of FNR partial ODC.

Author(s)

Hanfang Yang, Kun Lu, Xiang Lyu, Feifang Hu, Yichuan Zhao.

See Also

proc.est

Examples

library('pROC')
data(aSAH)
podc.est(aSAH$outcome, aSAH$s100b, method='expect',threshold=0.8 )

tpAUC documentation built on May 1, 2019, 8:44 p.m.