dprime_test: Test of simple hypothesis with the common d-prime

In perbrock/sensR: Thurstonian Models for Sensory Discrimination

Test of simple hypothesis with the common d-prime

Description

This function tests the hypothesis that the common d-prime is equal to or greater/less than a certain value, e.g. zero in a Wald or likelihood root test.

Usage

dprime_test(correct, total, protocol, conf.level = 0.95, dprime0 = 0,
    statistic = c("likelihood", "Wald"),
    alternative = c("difference", "similarity", "two.sided", "less", "greater"),
    estim = c("ML", "weighted.avg"))

Arguments

correct	a numeric vector of the number of correct answers; one element for each test.
total	a numeric vector of the total number of trials; one element for each test.
protocol	a character vector or factor naming the protocol used; one element for each test. Currently the following protocols are supported: "triangle", "duotrio", "threeAFC", "twoAFC", "tetrad".
conf.level	the confidence level for the confidence interval of the estimated common d-prime.
dprime0	Value of d-prime under the Null hypothesis. Non-negative numeric scalar.
statistic	the test statistic for computing the confidence interval as well as p-value.
alternative	the direction of the hypothesis test. "difference" and "similarity" are just alternative ways of specifying "greater" and "less" respectively.
estim	The estimation method for the common d-prime.

Details

The vectors correct, total and protocol have to be of the same length.

The function has a print method.

Value

an object of class "dprime_test" with the following elements

p.value	the p-value for the 'any-differences' test.
alternative	character naming the direction of the hypothesis test.

statistic	the name of the test statistic.
data	the data table produced by dprime_table.
conf.level	confidence level for the common d-prime.
conf.int	the confidence interval for the common d-prime.
estim	the estimation method for the common d-prime.
conf.method	the statistical method/test statistic used to compute the confidence interval for the common d-prime.

Author(s)

Rune Haubo B Christensen

See Also

dprime_compare, dprime_table, posthoc.dprime_compare.

Examples

n <- rep(40, 4)
x <- c(25, 25, 30, 35)
protocol <- c("triangle", "duotrio", "threeAFC", "twoAFC")
## Look at the data table with d-primes etc.:
dprime_table(x, n, protocol)

## Test of common d':
dprime_test(x, n, protocol)

## Another setting:
dprime_test(x, n, protocol, dprime0=2, statistic="Wald",
            alternative="less", estim="weighted.avg")

perbrock/sensR documentation built on Nov. 5, 2023, 10:41 a.m.