dimensionStability {EGAnet} | R Documentation |
bootEGA
Based on the bootEGA
results, this function
computes the stability of dimensions. This is computed by assessing the proportion of
times the original dimension is exactly replicated in across bootstrap samples
dimensionStability(bootega.obj, ...)
bootega.obj |
A |
... |
Additional arguments. Used for deprecated arguments from previous versions of dimStability |
Returns a list containing:
dimension.stability |
A list containing: |
item.stability |
Results from |
Hudson Golino <hfg9s at virginia.edu> and Alexander P. Christensen <alexpaulchristensen@gmail.com>
Christensen, A. P., & Golino, H. (2021). Estimating the stability of the number of factors via Bootstrap Exploratory Graph Analysis: A tutorial. Psych, 3(3), 479-500.
Christensen, A. P., Golino, H., & Silvia, P. J. (2020). A psychometric network perspective on the validity and validation of personality trait questionnaires. European Journal of Personality, 34(6), 1095-1108.
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.
# Load data
wmt <- wmt2[,7:24]
## Not run: # Estimate EGA network
## plot.type = "qqraph" used for CRAN checks
## plot.type = "GGally" is the default
ega.wmt <- EGA(data = wmt, model = "glasso", plot.type = "qgraph")
# Estimate bootstrap EGA
boot.wmt <- bootEGA(data = wmt, iter = 500, typicalStructure = TRUE,
plot.typicalStructure = TRUE, model = "glasso", plot.type = "qgraph",
type = "parametric", ncores = 2)
## End(Not run)
# Estimate stability statistics
res <- dimensionStability(boot.wmt)
res$dimension.stability
# Changing plot features (ggplot2)
## Changing colors (ignore warnings)
### qgraph Defaults
res$item.stability$plot +
ggplot2::scale_color_manual(values = rainbow(length(
res$dimension.stability$structural.consistency)))
### Pastel
res$item.stability$plot +
ggplot2::scale_color_brewer(palette = "Pastel1")
## Changing Legend (ignore warnings)
res$item.stability$plot +
ggplot2::scale_color_discrete(labels = "Intelligence")