# 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

 ```1 2 3 4 5 6 7``` ```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

`Sdt.fftree`
`Sdt.fftree`