discrimPwr {sensR} | R Documentation |
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.
discrimPwr(delta, sample.size, alpha = 0.05, method = c("duotrio", "threeAFC", "twoAFC", "triangle"), pd0 = 0, type = c("difference", "similarity"))
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 |
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.
The power.
Rune Haubo B Christensen and Per Bruun Brockhoff
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.
triangle
, twoAFC
,
threeAFC
, duotrio
,
discrim
, discrimSim
,
AnotA
, discrimSS
,
samediff
, findcr
## 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")