Description Usage Arguments Value Author(s) References See Also Examples
bootEGA
Estimates the number of dimensions of n bootstraps
using the empirical (partial) correlation matrix (parametric) or resampling from
the empirical dataset (nonparametric). It also estimates a typical
median network structure, which is formed by the median or mean pairwise (partial)
correlations over the n bootstraps.
1 2 3 
data 
Matrix or data frame.
Includes the variables to be used in the 
n 
Numeric integer.
Number of replica samples to generate from the bootstrap analysis.
At least 
model 
Character.
A string indicating the method to use.
Defaults to Current options are:

type 
Character. A string indicating the type of bootstrap to use. Current options are:

typicalStructure 
Boolean.
If 
plot.typicalStructure 
Boolean.
If 
ncores 
Numeric.
Number of cores to use in computing results.
Defaults to If you're unsure how many cores your computer has,
then use the following code: 
... 
Additional arguments to be passed to 
Returns a list containing:
n 
Number of replica samples in bootstrap 
boot.ndim 
Number of dimensions identified in each replica sample 
boot.wc 
Item allocation for each replica sample 
bootGraphs 
Networks of each replica sample 
summary.table 
Summary table containing number of replica samples, median, standard deviation, standard error, and 95% confidence intervals 
frequency 
Proportion of times the number of dimensions was identified (e.g., .85 of 1,000 = 850 times that specific number of dimensions was found) 
EGA 
Output of the original 
typicalGraph 
A list containing:

Hudson F. Golino <hfg9s at virginia.edu> and Alexander P. Christensen <[email protected]>
Christensen, A. P., & Golino, H. F. (2019). Estimating the stability of the number of factors via Bootstrap Exploratory Graph Analysis: A tutorial. PsyArXiv. doi:10.31234/osf.io/9deay
EGA
to estimate the number of dimensions of an instrument using EGA
and CFA
to verify the fit of the structure suggested by EGA using confirmatory factor analysis.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21  # Load data
wmt < wmt2[,7:24]
## Not run:
# bootEGA glasso example
boot.wmt < bootEGA(data = wmt, n = 500, typicalStructure = TRUE,
plot.typicalStructure = TRUE, model = "glasso", type = "parametric", ncores = 4)
## End(Not run)
# Load data
intwl < intelligenceBattery[,8:66]
## Not run:
# bootEGA TMFG example
boot.intwl < bootEGA(data = intelligenceBattery[,8:66], n = 500, typicalStructure = TRUE,
plot.typicalStructure = TRUE, model = "TMFG", type = "parametric", ncores = 4)
## End(Not run)

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