CheckAttr4Inclusion {RatingScaleReduction}

Check the next attribute for possible inclusion into AUC

Description

The attribute checked for AUC before it is added to the running total. The running total is used with the class (decision attribute) to compute AUC. The next attribute is added to the sequence of attributes having the MAX total AUC.

Usage

CheckAttr4Inclusion(attribute, D, plotCheck=FALSE, method=c("delong", "bootstrap",
"venkatraman", "sensitivity", "specificity"), boot.n,
alternative = c("two.sided", "less", "greater"))

Arguments

attribute

a matrix or data.frame containing attributes

D

the decision vector

plotCheck

If TRUE the plot with two ROC curves is created

method

the method to useas in the function roc.test{pROC}

boot.n

boostrap replication number

alternative

the alternative hipothesis

Value

test

the result of the roc.test as in the function roc.test from the package pROC

Author(s)

Waldemar W. Koczkodaj, Feng Li,Alicja Wolny-Dominiak

References

1. R. DeLong, D. M. DeLong, and D. L. Clarke-Pearson. Comparing the areas under two or more correlated receiver operating characteristic curves: a nonparametric approach. Biometrics, pages 837 - 845, 1988.

2. W.W. Koczkodaj, T. Kakiashvili, A. Szymanska, J. Montero-Marin, R. Araya, J. Garcia-Campayo, K. Rutkowski, D. Strzalka, How to reduce the number of rating scale items without predictability loss? Scientometrics,909(2):581-593(open access), 2017
https://link.springer.com/article/10.1007/s11192-017-2283-4

Examples

#creating the matrix of attributes and the decision vector
#must be as.numeric()
data(aSAH)
attach(aSAH)
is.numeric(aSAH)

attribute <-data.frame(as.numeric(gender), 
as.numeric(age), as.numeric(wfns), as.numeric(s100b), as.numeric(ndka))
colnames(attribute) <-c("a1", "a2", "a3", "a4", "a5")
decision <-as.numeric(outcome)

#deLong test, two-side alternative hiphotesis
CheckAttr4Inclusion(attribute, decision, method=c("delong"), 
alternative=c("two.side"))

#bootstrap, two-side alternative hiphotesis
#CheckAttr4Inclusion(attribute, decision, method=c("bootstrap"), boot.n=500)
#