| tetrad {sensR} | R Documentation |
Create tetrad binomial family
Description
Creates a binomial family object with the inverse link function equal to the psychometric function for the unspecified method of tetrads.
Usage
tetrad()
Value
A binomial family object for models. Among other things it inludes the
psychometric function as
linkinv and the inverse psychometric function (for direct
d-prime computation) as
linkfun.
Note
Several functions in this package makes use of functions in the tetrad family object, but it may also be used on its own—see the example below.
Author(s)
Rune Haubo B Christensen
References
Ennis, J. M., Ennis, D. M., Yip, D., & O'Mahony, M. (1998). Thurstonian models for variants of the method of tetrads. British Journal of Mathematical and Statistical Psychology, 51, pp. 205-215.
Ennis, J. M., & Jesionka, V. (2011). The power of sensory discrimination methods revisited. Journal of Sensory Studies, 26, pp. 371-382.
See Also
duotrio, twoAFC,
threeAFC, discrim,
discrimPwr, discrimSim,
AnotA, discrimSS,
samediff, findcr
Examples
## Estimating d-prime using glm for a Tetrad test:
xt <- matrix(c(10, 5), ncol = 2) ## data: 10 correct answers, 5 incorrect
res <- glm(xt ~ 1, family = tetrad)
summary(res)
## Equivalent to (Estimate and Std. Error):
discrim(10, 15, method="tetrad")
## Extended example plotting the profile likelihood
## data: 10 correct answers, 9 incorrect
xt <- matrix(c(10, 9), ncol = 2)
summary(res <- glm(xt ~ 1, family = tetrad))
N <- 100
dev <- double(N)
delta <- seq(1e-4, 3, length = N)
for(i in 1:N)
dev[i] <- glm(xt ~ -1 + offset(delta[i]),
family = tetrad)$deviance
plot(delta, exp(-dev/2), type = "l",
xlab = expression(delta),
ylab = "Normalized Profile Likelihood")
## Add Normal approximation:
lines(delta, exp(-(delta - coef(res))^2 /
(2 * vcov(res))), lty = 2)
## Add confidence limits:
level <- c(0.95, 0.99)
lim <- sapply(level, function(x) exp(-qchisq(x, df=1)/2) )
abline(h = lim, col = "grey")