RatingScaleReduction (version 1.2)

totalAuc: AUC of the running total of attributes

Description

AUC values are computed for all individual attributes. We sort them in an ascending order. We beging with the attribute having the largest AUC and add to it the second, third,... attribute until AUC of the total of them decreases.

Usage

totalAuc(attribute, D, plotT = FALSE)

Arguments

attribute

a matrix or data.frame containing attributes

D

the decision vector

plotT

If TRUE the plot is created: x - labels of atrributes, y - total AUC in ascending order

Value

ordered.attribute

ordered attribute matrix

total.auc

total AUC

item

ordered attribute labels

summary

a summary table

References

1. 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

2. T. Kakiashvili, W. W. Koczkodaj, and M. Woodbury-Smith. Improving the medical scale predictability by the pairwise comparisons method: Evidence from a clinical data study. Computer Methods and Programs in Biomedicine, 105(3), 2012 DOI: http://dx.doi.org/10.1016/j.cmpb.2011.09.011

3. X. Robin, N. Turck, A. Hainard, N. Tiberti, F. Lisacek, J.-C. Sanchez, and M. Muller. proc: an opensource package for r and s+ to analyze and compare roc curves. BMC Bioinformatics, 2011 https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-77

Examples

# NOT RUN {
#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)

#arrange start AUC in an ascending order and compute total AUC according to 
#Rating Scale Reduction procedure

tot <-totalAuc(attribute, decision, plotT=TRUE)
tot$summary
# }