Package: pcaPA
Title: Parallel Analysis for Ordinal and Numeric Data using Polychoric
        and Pearson Correlations with S3 Classes
Version: 2.0.1
Date: 2016-09-14
Author: Carlos A. Arias <caariasr22@gmail.com> and Victor H. Cervantes 
        <Herulor@gmail.com>.
Maintainer: Carlos A. Arias <caariasr22@gmail.com>
Depends: R (>= 3.3.0), polycor, ltm, stats, ggplot2, mc2d, sfsmisc
Description: A set of functions to perform parallel analysis for
        principal components analysis intended mainly for large data
        sets. It performs a parallel analysis of continuous, ordered
        (including dichotomous/binary as a special case) or mixed type
        of data associated with a principal components analysis.
        Polychoric correlations among ordered variables, Pearson
        correlations among continuous variables and polyserial
        correlation between mixed type variables (one ordered and one
        continuous) are used. Whenever the use of polyserial or
        polychoric correlations yields a non positive definite
        correlation matrix, the resulting matrix is transformed into
        the nearest positive definite matrix. This is a continued work 
        based on a previous version developed at the Colombian Institute 
        for the evaluation of education - ICFES.
License: GPL (>= 2)
NeedsCompilation: yes
Packaged: 2016-09-15 15:21:57 UTC; CarlosAndresArias
Repository: CRAN
Date/Publication: 2016-09-15 21:57:14
