an_parallel: Parallel Analysis
In SICSresearch/LatentREGpp: Item Response Theory Implemented in R and Cpp

Description Usage Arguments Details Value References Examples

Performs Horn's parallel analysis for a principal component.

1 2	an_parallel(x = NA, iterations = 0, centile = 0, seed = 0,mat = NA, n = NA)

`x`	a matrix or a dataframe that holds the test response data.
`iterations`	how many iterations are performed during the analysis. Amount of random datasets produced.
`centile`	a number between 1 and 99 indicating the centile used in estimating bias.
`seed`	seed used for the random data generation.
`mat`	a supplied correlation mtrix to use instead of x. If used, then n must be also supplied.
`n`	the number of observations. Required when a correlation matrix is supplied with the mat option.

Implementation of Horn's (1965) tecnique for evaluating the components retained in a principle component analysis (PCA). This procedure is an adaptation of the paran function in the Paran Package.

Retained Components a scalar integer representing the number of retained components.

Adjusted Eigenvalues a vector of the estimated adjusted eigenvalues.

Unadjusted Eigenvalues a vector of the eigenvalues of the observed data from an unrotated principal component analysis.

Bias a vector of the estimated bias of the unadjusted eigenvalues

John L. Horn (1965). A rationale and test for the number of factors in factor analysis. Psychometrika, Volume 30, Number 2, Page 179.

Dinno A. 2009. Exploring the Sensitivity of Horn's Parallel Analysis to the Distributional Form of Simulated Data. Multivariate Behavioral Research. 44(3): 362-388

## Not run: 
 data <- simulate_dichotomous(size.cluster = c(10),sample.size=1000)
 an_parallel(data$data, iterations = 100, centile = 99, seed = 12)

## End(Not run)