nMreg | 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 |
cor |
logical: if |
model |
character: |
details |
logical: if |
... |
variable: additionnal parameters to give to the
|
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
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=""))
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