nMreg {nFactors} | R Documentation |
This function computes the β indices, like their associated Student t and probability (Zoski and Jurs, 1993, 1996, p. 445). These three values can be used as three different indices for determining the number of components/factors to retain.
nMreg(x, cor=TRUE, model="components", details=TRUE, ...)
x |
numeric: a vector of eigenvalues, a matrix of
correlations or of covariances or a data.frame of data (eigenFrom) |
cor |
logical: if TRUE computes eigenvalues from a correlation
matrix, else from a covariance matrix |
model |
character: "components" or "factors" |
details |
logical: if TRUE also return detains about the computation for each eigenvalues. |
... |
variable: additionnal parameters to give to the eigenComputes
and cor or cov functions |
When the associated Student t test is applied, the following hypothesis
is considered:
(1) qquad qquad H_k: β (λ_1 ... λ_k) -
β (λ_{k+1} ... λ_p), (k = 3, ..., p-3) = 0
nFactors |
numeric: number of components/factors retained by the MREG procedures. |
details |
numeric: matrix of the details for each indices. |
Gilles Raiche
Centre sur les Applications des Modeles de Reponses aux Items (CAMRI)
Universite du Quebec a Montreal
raiche.gilles@uqam.ca, http://www.er.uqam.ca/nobel/r17165/
Zoski, K. and Jurs, S. (1993). Using multiple regression to determine the number of factors to retain in factor analysis. Multiple Linear Regression Viewpoints, 20(1), 5-9.
Zoski, K. and Jurs, S. (1996). An objective counterpart to the visual scree test for factor analysis: the standard error scree test. Educational and Psychological Measurement, 56(3), 443-451.
plotuScree
,
nScree
,
plotnScree
,
plotParallel
## SIMPLE EXAMPLE OF A MREG ANALYSIS data(dFactors) eig <- dFactors$Raiche$eigenvalues results <- nMreg(eig) results plotuScree(eig, main=paste(results$nFactors[1], ", ", results$nFactors[2], " or ", results$nFactors[3], " factors retained by the MREG procedures", sep=""))