| summary.fechner {fechner} | R Documentation |
Summary Method for Objects of Class fechner
Description
S3 method to summarize objects of the class fechner.
Usage
## S3 method for class 'fechner'
summary(object, level = 2, ...)
Arguments
object |
a required object of class |
level |
an optional numeric, integer-valued and greater than or
equal to |
... |
further arguments to be passed to or from other methods. They are ignored in this function. |
Details
The summary method outlines the results obtained from
Fechnerian scaling analyses. It computes the Pearson correlation
coefficient and the C-index (see Uenlue, Kiefer, and
Dzhafarov (2009))
C = \frac{2\sum (S - G)^2}{\sum S^2 + \sum G^2}
for specific (controlled by the argument level) stimuli pairs
with their corresponding S-index and G values.
The level of comparison refers to the minimum number of links
in geodesic loops. That is, choosing level n means that
comparison involves only those S-index and G values that
have geodesic loops containing not less than n links.
If there are no (off-diagonal) pairs of stimuli with geodesic loops
containing at least level links (in this case a summary is
not possible), summary.fechner stops with an error message.
The function summary.fechner returns an object of the class
summary.fechner (see ‘Value’), for which a
print method, print.summary.fechner, is
provided. Specific summary information details such as individual
stimuli pairs and their corresponding S-index and G
values can be accessed through assignment (see ‘Examples’).
Value
If the arguments object and level are of required
types, and if there are (off-diagonal) pairs of stimuli with
geodesic loops containing at least level links,
summary.fechner returns a named list, of the class
summary.fechner, consisting of the following four components:
pairs.used.for.comparison |
a data frame giving the pairs
of stimuli (first variable |
Pearson.correlation |
a numeric giving the value of the Pearson correlation coefficient if it exists, or a character string saying “Pearson's correlation coefficient is not defined” if it does not exist. |
C.index |
a numeric giving the value of the |
comparison.level |
a numeric giving the |
Author(s)
Thomas Kiefer, Ali Uenlue. Based on original MATLAB source by Ehtibar N. Dzhafarov.
References
Dzhafarov, E. N. and Colonius, H. (2006) Reconstructing distances among objects from their discriminability. Psychometrika, 71, 365–386.
Dzhafarov, E. N. and Colonius, H. (2007) Dissimilarity cumulation theory and subjective metrics. Journal of Mathematical Psychology, 51, 290–304.
Uenlue, A. and Kiefer, T. and Dzhafarov, E. N. (2009) Fechnerian scaling in R: The package fechner. Journal of Statistical Software, 31(6), 1–24. URL http://www.jstatsoft.org/v31/i06/.
See Also
plot.fechner, the S3 method for plotting objects of
the class fechner; print.fechner, the S3 method
for printing objects of the class fechner;
print.summary.fechner, the S3 method for printing
objects of the class summary.fechner; fechner,
the main function for Fechnerian scaling, which creates objects of
the class fechner. See also fechner-package
for general information about this package.
Examples
## Fechnerian scaling of dataset \link{wish}
f.scal.wish <- fechner(wish)
## results are summarized for comparison levels 2 and 5
summary(f.scal.wish)
summary(f.scal.wish, level = 5)
## accessing detailed summaries through assignment
str(detailed.summary.l1 <- summary(f.scal.wish))
detailed.summary.l5 <- summary(f.scal.wish, level = 5)
detailed.summary.l5$pairs.used.for.comparison[1, ]
## to verify the obtained summaries
f.scal.wish$geodesic.loops
f.scal.wish$S.index
f.scal.wish$overall.Fechnerian.distances