Description Usage Arguments Value Author(s) References Examples
Performs a principal component analysis (PCA) of interconstruct correlation
matrix. Various methods for rotation and methods for the calculation of the
correlations are available. Note that the number of factors
has to be specified. For more information on the PCA function itself type
?principal
.
1 2 3  constructPca(x, nfactors=3, rotate="varimax", method=c("pearson",
"kendall", "spearman"), trim=NA, digits=2, cutoff=0,
output=1)

x 

nfactors 
Number of components to extract (default is 
rotate 

method 
A character string indicating which correlation coefficient
is to be computed. One of 
trim 
The number of characters a construct is trimmed to (default is

digits 
Numeric. Number of digits to round to (default is

cutoff 
Loadings smaller than cutoff are not printed. 
output 
The type of output printed to the console. 
Invisibly returns a matrix of loadings on the principal components.
Mark Heckmann
Fransella, F., Bell, R. & Bannister, D. (2003). A Manual for Repertory Grid Technique (2. Ed.). Chichester: John Wiley & Sons.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18  ## Not run:
# data from grid manual by Fransella et al. (2003, p. 87)
# note that the construct order is different
constructPca(fbb2003, nf=2)
# surpress printing to console
m < constructPca(fbb2003, nf=2)
m
# no rotation
constructPca(fbb2003, rotate="none")
# using a different correlation matrix (Spearman)
constructPca(fbb2003, method="spearman")
## End(Not run)

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