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    Names: »dprime.1«

└─⟦a0efdde77⟧ Bits:30001252 EUUGD11 Tape, 1987 Spring Conference Helsinki
    └─ ⟦this⟧ »EUUGD11/stat-5.3/eu/stat/man/dprime.1« 

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.TH DPRIME 1 "October 1985" "\(co 1980 Gary Perlman" "|STAT" "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
.I dprime
can be given two arguments: the hit-rate and the false-alarm-rate,
for which it will print d' and beta.
Otherwise,
.I dprime
reads raw data from the standard input.
If raw data are input,
.I dprime
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
while the following can be used to indicate negative:
.ce
noise, no, 0
Upper case forms for the above are allowed.
.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 EXAMPLE
.nf
.ta .75i +.75i +.75i +.75i +.75i
dprime .7 .4     # will print
hr	far	dprime	beta	
0.70	0.40	0.78	0.90	
.fi
.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.