Package: random.polychor.pa
Type: Package
Title: A Parallel Analysis With Polychoric Correlation Matrices
Version: 1.1.3.3
Date: 2013-03-03
Author: Fabio Presaghi & Marta Desimoni
Maintainer: Fabio Presaghi <fabio.presaghi@uniroma1.it>
Description: The Function performs a parallel analysis using simulated
polychoric correlation matrices. The nth-percentile of the
eigenvalues distribution obtained from both the randomly
generated and the real data polychoric correlation matrices is
returned. A plot comparing the two types of eigenvalues (real
and simulated) will help determine the number of real
eigenvalues that outperform random data. The function is based
on the idea that if real data are non-normal and the polychoric
correlation matrix is needed to perform a Factor Analysis, then
the Parallel Analysis method used to choose a non-random number
of factors should also be based on randomly generated
polychoric correlation matrices and not on Pearson correlation
matrices. Version 1.1.1, fixed a minor bug in the regarding the
estimated time needed to complete the simulation. Also in this
version, the function is now able to manage supplied
data.matrix in which variables representing factors (i.e.,
variables with ordered categories) are present and may cause an
error when the Pearson correlation matrix is calculated.
Version 1.1.2 simply has updated the function that calculates
the polychoric correlation matrix due to changes in the psych()
package. Version 1.1.3 tackles two problems signalled by users:
1) the possibility to make available the results of simulation
for plotting them in other software. Now the random.polychor.pa
will show, upon request, all the data used in the scree-plot.
2) The function polichoric() of the psych() package does not
handle data matrices that include 0 as possible category and
will cause the function to stop with error. So a check for the
detection of the 0 code within the provided data.matrix is now
added and will cause the random.polychor.pa function to stop
with a warning message.
Depends: psych, nFactors, mvtnorm, MASS, boot, lattice, polycor,
sfsmisc
LazyLoad: yes
LazyData: yes
License: GPL (>= 2)
Encoding: latin1
Packaged: 2013-03-04 08:41:05 UTC; fabio
Repository: CRAN
Date/Publication: 2013-03-04 09:53:31
NeedsCompilation: no