sensR (version 1.5-2)

twoAFC: Create 2-AFC binomial family

Description

Creates a copy of the binomial family with the inverse link function changed to equal the 2-AFC psychometric function and correspondingly changed link function and derivative of the inverse link function.

Usage

twoAFC()

Value

A binomial family object for models. Among other things it inludes the psychometric function as linkinv and the inverse psychometric function (for direct dprime computation) as linkfun.

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, threeAFC, tetrad, duotrio, discrim, discrimPwr, discrimSim, AnotA, discrimSS, samediff, findcr

Examples

# NOT RUN {
## Estimating d-prime using glm for a 2-AFC test:
xt <- matrix(c(10, 5), ncol = 2) ## data: 10 correct answers, 5 incorrect
res <- glm(xt ~ 1, family = twoAFC)
summary(res)
## Equivalent to (Estimate and Std. Error):
discrim(10, 15, method="twoAFC")

# }
# NOT RUN {
## Extended example plotting the profile likelihood
## data: 10 correct and 8 incorrect:
xt <- matrix(c(10, 8), ncol = 2)
summary(res <- glm(xt ~ 1, family = twoAFC))
N <- 100
dev <- double(N)
level <- c(0.95, 0.99)
delta <- seq(1e-4, 3, length = N)
for(i in 1:N)
  dev[i] <- glm(xt ~ -1 + offset(delta[i]),
                family = twoAFC)$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:
lim <- sapply(level, function(x)
              exp(-qchisq(x, df=1)/2) )
abline(h = lim, col = "grey")

# }