rocbc (version 3.2.0)

rocboxcoxCI: Inference around the sensitivity at a given specificity (and vice versa) for a single Box-Cox transformed biomarker

Description

This function applies the Box-Cox transformation and provides the ability to do inferences for the sensitivity at a given specificity (and vice versa).

Usage

rocboxcoxCI(marker, D, givenSP, givenSE, alpha, plots)

Value

SPandCIs

The specificity values and the CIs around them.

SEandCIs

The sensitivity values and the CIs around them.

SEvalues

The sensitivity values provided by the user at which the specificity was calculated. If the user did not provide any sensitivity values, this argument should be set to NA.

SPvalues

The specificity values provided by the user at which the sensitivity was calculated. If the user did not provide any specificity values, this argument should be set to NA.

Arguments

marker

A vector of length n that contains the biomarker scores of all individuals.

D

A vector of length n that contains the true disease status of an individual, where 0 denotes a healthy/control individual, and 1 denotes a diseased individual.

givenSP

A vector of specificity values that the user wants to fix/set, at which the sensitivity is to be estimated. In this case, the ‘givenSE’ argument needs to be set to NA.

givenSE

A vector of sensitivity values that the user want to fix/set, at which the specificity is to be estimated. In this case, the ‘givenSP’ argument needs to be set to NA.

alpha

Nominal level used to calculate the confidence intervals. A common choice is 0.05.

plots

Valid inputs are "on" and "off". When set to "on", it returns both (1) the Box-Cox based ROC plot along with pointwise 95% confidence intervals for the full spectrum of FPRs and (2) a second plot that visualizes the confidence intervals at the given sensitivities or specificities.

Author

Leonidas Bantis

References

Bantis LE, Feng Z. (2016). Comparison of two correlated ROC curves at a given specificity or sensitivity level. Statistics in Medicine, 35(24):4352-4367. https://doi.org/10.1002/sim.7008

Box GEP, Cox DR. (1964). An Analysis of Transformations. Journal of the Royal Statistical Society. 26(2):211-252. https://www.jstor.org/stable/2984418

Examples

set.seed(123)
x <- rgamma(100, shape=2, rate = 8)
y <- rgamma(100, shape=2, rate = 4)
scores <- c(x,y)
D=c(pracma::zeros(1,100), pracma::ones(1,100))
givenSP=c(0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9)
givenSE=NA
out=rocboxcoxCI(marker=scores, D, givenSP=givenSP, givenSE=NA, alpha=0.05, plots="on")