REREFACT (version 1.0)

correct_psi: Re-orders and/or re-signs as needed within the estimated covariance matrix for the vector of residuals for eta for each replication

Description

The correct_psi function accomplishes Step 4 of the algorithm with regard to replications of the estimated covariance matrix for the vector of residuals for eta. More specifically, the correct_psi function re-orders and/or re-signs as needed within the estimated covariance matrix for the vector of residuals for eta for each replication of a simulation study with exploratory factor analysis.

Usage

correct_psi(P_data, rep, n.eta, sample_psi)

Arguments

P_data

a list containing the correct permutation matrix, P_i, for each replication.

rep

the number of replications.

n.eta

the total number of latent variables within eta.

sample_psi

a list containing replications of the estimated covariance matrix for the vector of residuals for eta.

Details

The correct_psi function uses P to re-order and/or re-sign as needed within the estimated covariance matrix for the vector of residuals for eta for each replication of a simulation study with exploratory factor analysis. This function returns a list, correct_psi, of the re-ordered and/or re-signed estimated covariance matrix for the vector of residuals for eta for each replication and saves the list as a text file to the designated working directory.

References

Myers, N. D., Ahn, S., Lu, M., Celimli, S., Zopluoglu, C. (2016). REREFACT: An R package for reordering and reflecting factors for simulation studies with Exploratory Factor Analysis. Manuscript submitted for publication.

See Also

rerefact, correct_alpha, correct_beta, correct_lambda, correct_gamma

Examples

# Load the P for Example 1 from Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

data(P_efa)

# Load 200 replications of the estimated covariance matrix 
# for the vector of residuals for eta provided by 
# replication numbers 1 through 100 and 4701 through 4800 in Example 1 from 
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

data(sample_psi_efa)

# Specify the following arguments within the correct_psi function for Example 1 from 
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

correct_psi(P_data=P_efa, rep=200, n.eta=3, sample_psi=sample_psi_efa)

# Load the P for Example 2 from Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

data(P_esem)

# Load 200 replications of the estimated covariance matrix
# for the vector of residuals for eta provided by 
# replication numbers 1 through 100 and 4701 through 4800 in Example 2 from 
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

data(sample_psi_esem)

# Specify the following arguments within the correct_psi function for Example 2 from
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).

correct_psi(P_data=P_esem, rep=200,n.eta=4, sample_psi=sample_psi_esem)