dprime: Calculates Signal Detection Theory indices.

In neuropsychology: Toolbox for Psychologists, Neuropsychologists and Neuroscientists

Description

Calculates the d', the beta, the A' and the B”D based on the signal detection theory (SRT). See Pallier (2002) for the algorithms.

Usage

dprime(n_hit, n_miss, n_fa, n_cr)

Arguments

n_hit	Number of hits.
n_miss	Number of misses.
n_fa	Number of false alarms.
n_cr	Number of correct rejections.

Details

For d' and beta, adjustement for extreme values are made following the recommandations Hautus (1995).

Value

A list containing 4 objects.

dprime	The d'. d' reflects the distance between the two distributions: signal, and signal+noise and corresponds to the Z value of the hit-rate minus that of the false-alarm rate.
beta	The beta. The value for beta is the ratio of the normal density functions at the criterion of the Z values used in the computation of d'. This reflects an observer's bias to say 'yes' or 'no' with the unbiased observer having a value around 1.0. As the bias to say 'yes' increases, resulting in a higher hit-rate and false-alarm-rate, beta approaches 0.0. As the bias to say 'no' increases, resulting in a lower hit-rate and false-alarm rate, beta increases over 1.0 on an open-ended scale.
aprime	The A'. Non-parametric estimate of discriminability. An A' near 1.0 indicates good discriminability, while a value near 0.5 means chance performance.
bppd	The B”D. Non-parametric estimate of bias. A B”D equal to 0.0 indicates no bias, positive numbers represent conservative bias (i.e. a tendency to answer 'no'), negative numbers represent liberal bias (i.e. a tendency to answer 'yes'). The maximum absolute value is 1.0.
c	The Criterion. the number of standard deviations from the midpoint between these two distributions, i.e. a measure on a continuum from "conservative" to "liberal".

Examples

n_hit <- 9
n_miss <- 1
n_fa <- 2
n_cr <- 7

indices <- dprime(n_hit, n_miss, n_fa, n_cr)

Example output

Loading required package: tidyverse
Loading tidyverse: ggplot2
Loading tidyverse: tibble
Loading tidyverse: tidyr
Loading tidyverse: readr
Loading tidyverse: purrr
Loading tidyverse: dplyr
Conflicts with tidy packages ---------------------------------------------------
filter(): dplyr, stats
lag():    dplyr, stats
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Welcome to neuropsychology v0.5.0 (c) Dominique Makowski.
See documentation on https://www.rdocumentation.org/packages/neuropsychology
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neuropsychology documentation built on May 2, 2019, 2:13 p.m.