pcaPA: Parallel Analysis for Ordinal and Numeric Data using Polychoric and Pearson Correlations with S3 Classes
Version 2.0.2

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.

AuthorCarlos A. Arias <caariasr22@gmail.com> and Victor H. Cervantes <Herulor@gmail.com>.
Date of publication2016-09-16 18:15:52
MaintainerCarlos A. Arias <caariasr22@gmail.com>
LicenseGPL (>= 2)
Version2.0.2
Package repositoryView on CRAN
InstallationInstall the latest version of this package by entering the following in R:
install.packages("pcaPA")

Getting started

README.md

Popular man pages

CalculatePABinary: Parallel Analysis for Dichotomous Data.
CalculatePAMixed: Parallel Analysis for numeric and ordered mixed data.
coef.PA: Eigenvalue and percentile extraction of a '"PA"' object.
CountEigen.PA: Number of observed eigenvalues that exceed a given set of...
PA: General function to perform parallel analysis of continuous,...
plot.PA: Plot method for PA objects.
sim2plData: Simulated data conforming to the 2pl model.
See all...

All man pages Function index File listing

Man pages

CalculatePABinary: Parallel Analysis for Dichotomous Data.
CalculatePAContinuous: Parallel Analysis for continuous data.
CalculatePAMixed: Parallel Analysis for numeric and ordered mixed data.
CalculatePAOrdered: Parallel Analysis for Ordered Data.
Check.PA: Verifies that an object belongs to the '"PA"' class.
coef.PA: Eigenvalue and percentile extraction of a '"PA"' object.
CountEigen.PA: Number of observed eigenvalues that exceed a given set of...
mixedScience: Simulated data from a normal distribution added to the...
PA: General function to perform parallel analysis of continuous,...
plot.PA: Plot method for PA objects.
print.PA: Print method for PA objects.
quantile.PA: Generate new quantiles based on given percentiles for a PA...
sim2plData: Simulated data conforming to the 2pl model.
simRaschData: Simulated data conforming to the Rasch Model.

Functions

CalculatePABinary Man page Source code
CalculatePAContinuous Man page Source code
CalculatePAMixed Man page Source code
CalculatePAOrdered Man page Source code
Check.PA Man page Source code
CountEigen.PA Man page Source code
PA Man page Source code
coef.PA Man page Source code
mixedScience Man page
plot.PA Man page Source code
print.PA Man page Source code
quantile.PA Man page Source code
sim2plData Man page
simRaschData Man page

Files

src
src/Makevars
src/Cpolychoric.cpp
src/Makevars.win
NAMESPACE
data
data/mixedScience.rda
data/sim2plData.rda
data/simRaschData.rda
R
R/CountEigenPA.R
R/coef.PA.R
R/quantile.PA.R
R/PA.R
R/print.PA.R
R/CalculatePAMixed.R
R/CalculatePABinary.R
R/CalculatePAContinuous.R
R/CalculatePAOrdered.R
R/Check.PA.R
R/plot.PA.R
README.md
MD5
DESCRIPTION
man
man/CalculatePAOrdered.Rd
man/quantile.PA.Rd
man/PA.Rd
man/CountEigen.PA.Rd
man/coef.PA.Rd
man/simRaschData.Rd
man/CalculatePAContinuous.Rd
man/sim2plData.Rd
man/Check.PA.Rd
man/CalculatePAMixed.Rd
man/plot.PA.Rd
man/mixedScience.Rd
man/CalculatePABinary.Rd
man/print.PA.Rd
pcaPA documentation built on May 19, 2017, 4:50 p.m.

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