samediff: Computation of tau and dprime for same different test

In perbrock/sensR: Thurstonian Models for Sensory Discrimination

Computation of tau and dprime for same different test

Description

Computation of tau and dprime and their uncertainties for the same different test using maximum likelihood.

Usage

samediff(nsamesame, ndiffsame, nsamediff, ndiffdiff, VCOV = TRUE)

Arguments

nsamesame	The number of same-answers on same-samples
ndiffsame	The number of different-answers on same-samples
nsamediff	The number of same-answers on different-samples
ndiffdiff	The number of different-answers on different-samples
VCOV	Should the variance-covariance matrix of the parameters be computed. Defaults to TRUE.

Details

The function computes the maximum likelihood estimates of tau and delta.

Value

An object of class samediff with elements

coef	named vector of coefficients (d-prime and tau)
vcov	variance-covariance matrix of the coefficients
se	named vector with standard error of the coefficients (standard error of d-prime)
data	a named vector with the data supplied to the function
test	a string with the name of the test (same-different)
call	the matched call
convergence	convergence indicater. 0 indicates convergence. For error codes see optim.
logLik	Value of the log-likelhood at the MLE of the parameters.
case	A case indicator for internal use

Author(s)

Rune Haubo B Christensen

References

Christensen, R.H.B., Brockhoff, P.B. (2009). Estimation and inference in the same-different test. Food, Quality and Preference, 20 pp. 514–520

Examples

# data: 8 of the same samples were judged to be same
#       5 of the same samples were judged to be different
#       4 of the different samples were judged to be same
#       9 of the different samples were judged to be different

samediff(8, 5, 4, 9)

perbrock/sensR documentation built on Nov. 5, 2023, 10:41 a.m.