Generate a response style data set from a specific correlation matrix, clean the data with constrained dual scaling and report the original, cleaned and contaminated correlation matrices in a list.
genPCA(
nr.indv = rep(100, 5),
m = 10,
q = 7,
r = 3,
err.coeff = 0.1,
alphamat = rbind(c(0.5, 2, 4), c(10, 2, 10), c(1, 2, 1), c(4, 2, 0.5), c(0.1, 2,
0.1))[1:length(nr.indv), ],
randomize = TRUE,
...
)A list with components:
Correlation matrix from which the sample was generated
Correlation matrix for the cleaned data
Correlation matrix for the contaminated data
Vector; number of individuals in each response style group.
It is passed to simpca.
scalar; Number of items.
scalar; Number of rating categories, such that the rating scale is
1:q.
scalar; Rank of simulated correlation matrices.
scalar; Standard deviation used in simulations that is
passed on to simpca.
matrix; Contains the spline parameters for the different
response styles that is passed to simpca.
logical; See simpca.
Arguments passed to cds.
Pieter C. Schoonees