sensR (version 1.2.2)

discrim: Sensory discrimination analysis

Description

Computes the d-prime, its standard error and P-value for the hypothesis of no sensory difference for any of four methods: 2-AFC, 3-AFC, duotrio and triangle tests.

Usage

discrim(success, total,
        method = c("duotrio", "threeAFC", "twoAFC", "triangle"),
        pd0 = 0, type = c("difference", "similarity"), ...)

## S3 method for class 'discrim':
print(x, digits = getOption("digits"), alpha = 0.05, ...)

Arguments

success

the number of correct answers

total

the total number of answers (sample size)

method

the discrimination protocol. Four allowed values: "twoAFC", "threeAFC", "duotrio", "triangle"

pd0

the proportion of discriminators in the population of interest

type

the type of test

x

an object of class "discrim"

alpha

the allowed type I level of the Wald based confidence interval

digits

number of digits in resulting table of results

...

additional arguments passed to glm

Value

• An object of class discrim with elements
• coefficients
  named vector of coefficients (d-prime and tau)
• res.glm
  the glm-object from the fitting process
• 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
• p.value
  one-tailed exact binomial p-value
• test
  a string with the name of the test for the print method
• call
  the matched call

Details

The p-value for the standard one-tailed difference test of "no difference" is obtained with pd0 = 0. The probability under the null hypothesis is given by pd0 + p0 * (1 - pd0) where p0 is the guessing probability defined by the method argument. The function uses the one of the dedicated binomial families and the base function glm

References

Brockhoff, P.B. and Christensen, R.H.B (2010). Thurstonian models for sensory discrimination tests as generalized linear models. Food Quality and Preference, 21, pp. 330-338.

See Also

triangle, twoAFC, threeAFC, duotrio, discrimPwr, discrimSim, discrimSS, samediff, AnotA, findcr

Examples

## Running the simple discrimination (differens) tests:
discrim(10, 15, method = "twoAFC")
discrim(10, 15, method = "threeAFC")
discrim(10, 15, method = "duotrio")
discrim(10, 15, method = "triangle")

## A similarity test where less than chance successes are obtained:
discrim(20, 75, "triangle", pd0 = .2, type = "simil")