Description Usage Arguments Details Value Author(s) See Also Examples
This function tests the hypothesis that the common dprime is equal to or greater/less than a certain value, e.g. zero in a Wald or likelihood root test.
1 2 3 4  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"))

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:

conf.level 
the confidence level for the confidence interval of the estimated common dprime. 
dprime0 
Value of dprime under the Null hypothesis. Nonnegative numeric scalar. 
statistic 
the test statistic for computing the confidence interval as well as pvalue. 
alternative 
the direction of the hypothesis test. 
estim 
The estimation method for the common dprime. 
The vectors correct
, total
and protocol
have to
be of the same length.
The function has a print method.
an object of class "dprime_test"
with the following elements
p.value 
the pvalue for the 'anydifferences' test. 
alternative 
character naming the direction of the hypothesis test. 
statistic 
the name of the test statistic. 
data 
the data table produced by 
conf.level 
confidence level for the common dprime. 
conf.int 
the confidence interval for the common dprime. 
estim 
the estimation method for the common dprime. 
conf.method 
the statistical method/test statistic used to compute the confidence interval for the common dprime. 
Rune Haubo B Christensen
dprime_compare
, dprime_table
,
posthoc.dprime_compare
.
1 2 3 4 5 6 7 8 9 10 11 12  n < rep(40, 4)
x < c(25, 25, 30, 35)
protocol < c("triangle", "duotrio", "threeAFC", "twoAFC")
## Look at the data table with dprimes 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")

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