EGA
residualEGA
Estimates the number of dimensions after controlling for wording effects.
EGA is applied in the residual of a random intercept item factor model (RIIFA) with one method factor and one substantive factor.
residualEGA(data, manifests, lat, negative.items, plot = TRUE)
Matrix or data frame.
Includes the variables to be used in the residualEGA
analysis
Character vector. Vector indicating the names of the variables (items) to be used in the analysis.
Numeric integer. Number of latent factors to be estimated. Only one substantive latent factor is recommended in the current version of the function.
Numeric vector A numeric vector indicating the column of the negative items.
Boolean.
If TRUE
, returns a plot of the residualized network and its estimated dimensions.
Defaults to TRUE
Returns a list containing:
OpenMX model
OpenMX results
OpenMX standardized parameters
Residual matrix
Results of the residualized EGA
Fit metrics of the network structure, calculated using the ggmfit function of the
qgraph
package
Loadings of the wording effects
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.
# NOT RUN {
data <- optimism
# }
# NOT RUN {
# resEGA example
opt.res <- residualEGA(data = data, manifests = colnames(optimism),
lat = 1, negative.items = c(3,7,9), plot = TRUE)
# Fit:
opt.res$Fit
# }
# NOT RUN {
# }
Run the code above in your browser using DataLab