sensR (version 1.2.2)

discrimPwr: 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

Value

• The power.

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.

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")