mca.eigen.fix
A function for correcting the eigenvalues and output from multiple correspondence analysis (MCA, epMCA)
mca.eigen.fix(DATA, mca.results, make_data_nominal = TRUE, numVariables = NULL,
correction = c("b"), symmetric = FALSE)DATA |
original data (i.e., not transformed into disjunctive coding) |
mca.results |
output from |
make_data_nominal |
a boolean. Should DATA be transformed into disjunctive coding? Default is TRUE. |
numVariables |
the number of actual measures/variables in the data (typically the number of columns in DATA) |
correction |
which corrections should be applied? "b" = Benzécri correction, "bg" = Greenacre adjustment to Benzécri correction. |
symmetric |
a boolean. If the results from MCA are symmetric or asymmetric factor scores. Default is FALSE. |
mca.results |
a modified version of mca.results. Factor scores (e.g., $fi, $fj), and $pdq are updated based on corrections chosen. |
Derek Beaton
Benzécri, J. P. (1979). Sur le calcul des taux d'inertie dans l'analyse d'un questionnaire. Cahiers de l'Analyse des Données, 4, 377-378.
Greenacre, M. J. (2007). Correspondence Analysis in Practice. Chapman and Hall.
data(mca.wine)
#No corrections used in MCA
mca.wine.res.uncor <- epMCA(mca.wine$data,correction=NULL)
data <- mca.wine$data
expo.output <- mca.wine.res.uncor$ExPosition.Data
#mca.eigen.fix with just Benzécri correction
mca.wine.res.b <- mca.eigen.fix(data, expo.output,correction=c('b'))
#mca.eigen.fix with Benzécri + Greenacre adjustment
mca.wine.res.bg <- mca.eigen.fix(data,expo.output,correction=c('b','g'))Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.