Description Usage Arguments Details Author(s) References Examples
Obtain the standardized distance between the two probability distributions, known as d' or sensitivity index.
1 2 3 4 5 6 7 8 |
x |
a data frame or matrix containing samples from two multivariate normal distributions. |
category |
a vector or factor of labels of populations to which the samples belong |
response |
a vector or factor specifying the participant's classification responses for each samples |
par |
object of class |
zlimit |
numeric. The z-scores (or discriminant scores) beyond the specified value will be truncated and replaced with that value. Default to |
type |
a character string specifying the type of d' to be returned. If |
means |
a list of numeric vectors containing the means of two distributions |
covs |
a matrix or a list of matrices containing the variance-covariance matrix of the two distributions |
noise |
numeric. perceptual and criterial noise expressed as standard deviation. Default to |
The function dprime
estimates d' from sample data sets, whereas the function dprimef
calculates it from population parameters.
In dprime
, if any parts of the argument par
are missing, the function will estimate an optimal linear decision bound from supplied x
and category
. The argument response
is not used if type
is SampleIdeal
.
Author of the original Matlab routines: Leola Alfonso-Reese
Author of R adaptation: Kazunaga Matsuki
Alfonso-Reese, L. A. (2006) General recognition theory of categorization: A MATLAB toolbox. Behavior Research Methods, 38, 579-583.
1 2 3 4 5 6 7 |
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.