Sdt: Wrapper function sdt

In fftrees: Fast- and Frugal Tree Analysis

Description

Wrapper function sdt

Creates a 'Signal Detection Theory' vector

Creates a 'Signal Detection Theory' vector

Usage

Sdt(hi, ...)

## Default S3 method:
Sdt(hi, fa, mi, cr)

## S3 method for class 'logical'
Sdt(criterion, prediction)

Arguments

hi	numeric; hits / true positives
...	further parameter
fa	numeric; false alarms / false positives
mi	numeric; misses / false negatives
cr	numeric; correct rejection / true negatives
criterion	logical vector
prediction	logical vector

Details

This function returns: hitrate (sensitivity/TPR), specifity (true negative rate/SPC), false alarm rate (fall-out/FPR), false discovery rate (FDR), an estimated d' (qnorm(hitrate)-qnorm(false alarm rate)) and the MCC, the "Matthews correlation efficient", c-bias (c < 0 -> liberal; c > 0 -> conservative).

Some results are adjusted, to make them calculatable. If one of the contingency-values hi, fa, mi or cr equals zero, all of them will gain .25: Sdt(1, 0, 2, 4) equals Sdt(1.25, .25, 2.25, 4.25). The denominator of the Matthews correlation coefficient is adjusted to 1 if (hi + fa) == 0, (hi + mi) == 0, (fa + cr) == 0 or (cr + mi) == 0.

Value

numeric vector with signal-detection values

numeric vector with signal-detection values

References

http://kangleelab.com/signal detection theory.html http://en.wikipedia.org/wiki/Matthews_correlation_coefficient

See Also

Sdt.fftree

Sdt.fftree

fftrees documentation built on May 2, 2019, 5:48 p.m.