discrimPwr {sensR}R Documentation

Sensory discrimination power analysis

Description

Computes the power of the hypothesis test of no sensory difference for any one of four methods: 2-AFC, 3-AFC, duotrio and triangle tests given the underlying sensory difference delta, the type I test level and the sample size.

Usage

discrimPwr(delta, sample.size, alpha = 0.05,
           method = c("duotrio", "threeAFC", "twoAFC", "triangle"),
           pd0 = 0, type = c("difference", "similarity"))

Arguments

delta the underlying sensory difference (non-negative)
sample.size the sample size (a positive integer)
alpha the type I level of the test (must be between zero and one)
method the discrimination test protocol. Four allowed values: "twoAFC", "threeAFC", "duotrio", "triangle"
pd0 the proportion of discriminators in the population of interest
type the type of test

Details

The power of 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 one of the dedicated binomial families.

Value

The power.

Author(s)

Rune Haubo B Christensen and Per Bruun Brockhoff

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, discrim, discrimSim, AnotA, discrimSS, samediff, findcr

Examples

## Finding the power of a discrimination test with a sensory delta of 1,
## a sample of size 30 and a type I level of .05:
discrimPwr(1, 30, 0.05, "twoAFC")
discrimPwr(1, 30, 0.05, "threeAFC")
discrimPwr(1, 30, 0.05, "duotrio")
discrimPwr(1, 30, 0.05, "triangle")

## A similarity example:
discrimPwr(.2, 100, method = "triangle", pd0 = .2, type = "simil")


[Package sensR version 1.1.0 Index]