https://github.com/cran/nFactors
Tip revision: 592b098fc786911733da1c1953e58c9d1c2e9517 authored by Gilles Raiche on 10 April 2010, 00:00:00 UTC
version 2.3.3
version 2.3.3
Tip revision: 592b098
nFactors-package.rd
\name{nFactors-package}
\alias{nFactors-package}
\alias{nFactors}
\docType{package}
\title{ Parallel Analysis and Non Graphical Solutions to the Cattell Scree Test}
\description{
Indices, heuristics and strategies to help determine the number of factors/components to retain:
\enumerate{
\item{- }{ Acceleration factor (\emph{noc} with or without Parallel Analysis) }
\item{- }{ Optimal Coordinates (\emph{noc} with or without Parallel Analysis) }
\item{- }{ Parallel analysis (components, factors and bootstrap) }
\item{- }{ \eqn{\lambda >= \bar{\lambda}} (Kaiser, CFA and related rule) }
\item{- }{ Cattell-Nelson-Gorsuch (\emph{CNG}) }
\item{- }{ Zoski and Jurs Multiple regression (\eqn{\beta}, \emph{t} and \emph{p}) }
\item{- }{ Zoski and Jurs standard error of the regression coefficient (sescree, \eqn{S_{Y \bullet X}}) }
\item{- }{ Nelson \eqn{R^2} }
\item{- }{ Bartlett \eqn{\chi^2} }
\item{- }{ Anderson \eqn{\chi^2} }
\item{- }{ Lawley \eqn{\chi^2} and }
\item{- }{ Bentler-Yuan \eqn{\chi^2}. }
}
}
\details{
\tabular{ll}{
Package: \tab nFactors \cr
Type: \tab Package \cr
Version: \tab 2.3.2 \cr
Date: \tab 2010-04-10 \cr
Depends: \tab R (>= 2.9.2), MASS, psych, boot \cr
License: \tab GPL \cr
}
}
\author{
Gilles Raiche \cr
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI) \cr
Universite du Quebec a Montreal\cr
\email{raiche.gilles@uqam.ca}, \url{http://www.er.uqam.ca/nobel/r17165/} \cr \cr
David Magis \cr
Departement de mathematiques \cr
Universite de Liege \cr
\email{David.Magis@ulg.ac.be}
}
\references{
Raiche, G., Riopel, M. and Blais, J.-G. (2006). \emph{Non graphical solutions
for the Cattell's scree test}. Paper presented at the International Annual
meeting of the Psychometric Society, Montreal.
[\url{http://www.er.uqam.ca/nobel/r17165/RECHERCHE/COMMUNICATIONS/}]
}
\seealso{
Other packages are also very useful for principal component and factor analysis. The \emph{R} psychometric view is instructive at this point.
See \url{http://cran.stat.sfu.ca/web/views/Psychometrics.html} for further details.
}
\keyword{ package }