simpca {cds}

Simulate Data with a Specific Principal Components Structure and Response Style Contamination

Description

Simulate normally distributed data with specific covariance structure and randomly sampled means. Adds response style contamination.

Usage

simpca(nr.indv = rep(200, 5), m = 10, q = 7, R = rcormat(m = m),
  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 = FALSE)

Arguments

nr.indv

Numeric vector of group sizes.

m

Integer; then number of variables to simulate.

q

Integer; the rating scale used 1:q.

R

List with entry named 'R' which is the simulated correlation matrix

err.coeff

Standard error for each variable, added unto R.

alphamat

Matrix containing splines coefficients for te construction of respone styles.

randomize

logical; should the rows of the data be randomly permuted or not?