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⟦c945e36b5⟧ TextFile

    Length: 1827 (0x723)
    Types: TextFile
    Names: »dprime.1«

Derivation

└─⟦87ddcff64⟧ Bits:30001253 CPHDIST85 Tape, 1985 Autumn Conference Copenhagen
    └─ ⟦this⟧ »cph85dist/stat/doc/man/dprime.1« 

TextFile

.TH DPRIME 1 "March 5, 1985" "UNIX|STAT 5.0" "UNIX User's Manual"
.SH NAME
dprime \- compute d' and beta for signal detection data
.SH SYNOPSIS
.B dprime
[hit-rate false-alarm-rate]
.SH DESCRIPTION
\fIdprime\fR can be given two arguments: the hit-rate and the false-alarm-rate,
for which it will print d' and beta.
Otherwise, \fIdprime\fR reads raw data from the standard input.
If raw data are input,
\fIdprime\fR assumes a two column input in which the first column tells whether
signal+noise or just noise were presented,
and the second column tells how the observer responded.
The following strings can be used to indicate affirmative answers
.ce
signal, yes, 1, 1.0000
while the following can be used to indicate negative:
.ce
noise, no, 0, 0.0000
.SH ALGORITHM
.PP
The value for d' is the Z value of the hit-rate
minus that of the false-alarm-rate.
.ce
d' = Z(hr) - Z(far)
This reflects the distance between the two distributions:
signal, and signal+noise.
Though Z values can have any real value,
normally distributed ones are between -2 and 2 about 95% of the time,
so differences of twice that would be rare.
.PP
The value for beta is the ratio of the normal density functions
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.
A major reason for doing a signal detection analysis is to get a measure
of discrimination that is constant over observer biases,
but the invariance of beta is often not certain.
.SH AUTHOR
Gary Perlman
.SH SEE\ ALSO
unixstat(1)
.SH REFERENCE
The chapter on Theory of Signal Detection in
Coombs, Dawes, and Tversky's
.I "Mathematical psychology,"
1970, Academic Press.
.SH BUGS
The program has not been tested extensively.
.SH KEYWORDS
statistics, data analysis, psychology, perception