podc: Partial ODC Estimation and Inference

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

Description

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

Usage

podc(response, predictor, threshold = 0.9, method = "MW", ci = TRUE,
  cp = 0.95, 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 0/1, 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 FNR-pODC. MW: Mann-Whitney statistic. expect: method in (2.2) Wang and Chang, 2011. jackknife: jackknife method in Yang et al., 2017.
ci	logic; compute the confidence interval of estimation?
cp	numeric; coverage probability of confidence interval.
smooth	if TRUE, the ODC curve is passed to smooth to be smoothed.

Details

This function estimates and infers 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 and Inference of FNR partial ODC.

Author(s)

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

See Also

podc.est, podc.ci

Examples

library('pROC')
data(aSAH)
podc(aSAH$outcome, aSAH$s100b,threshold=0.9, method='expect',ci=TRUE, cp=0.95 )

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