Description Usage Arguments Details Author(s) References See Also Examples
The correct_alpha function accomplishes Step 4 of the algorithm with regard to replications of the estimated intercept or mean vector. More specifically, the correct_alpha function re-orders and/or re-signs as needed within the estimated intercept or mean vector for each replication so that all replications uniformly follow the order and sign pattern defined by the population values.
1 | correct_alpha(P_data, rep, n.eta, sample_alpha)
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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_alpha |
a list containing replications of the estimated intercept or mean vector. |
The correct_alpha function uses P to re-order and/or re-sign as needed within the estimated intercept or mean vector for each replication of a simulation study with exploratory factor analysis. This function returns a list, correct_alpha, of the re-ordered and/or re-signed estimated intercept or mean vector for each replication and saves the list as a text file to the designated working directory.
Soyeon Ahn, Cengiz Zopluoglu, Seniz Celimli, Min Lu, & Nicholas D. Myers
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.
rerefact
, correct_beta
, correct_lambda
, correct_psi
, correct_gamma
1 2 3 4 5 6 7 8 9 10 11 12 13 14 | # Load the P for Example 2 from Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).
data(P_esem)
# Load 200 replications of the estimated intercept or mean vector provided by replication
# numbers 1 through 100 and 4701 through 4800 in Example 2 from
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).
data(sample_alpha_esem)
# Specify the following arguments within the correct_alpha function for Example 2 from
# Myers, Ahn, Lu, Celimli, and Zopluoglu (2016).
correct_alpha(P_data=P_esem, rep=200, n.eta=4, sample_alpha=sample_alpha_esem)
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