esem_efa {esem} | R Documentation |
Exploratory factor analysis (EFA) for ESEM
Description
Exploratory factor analysis (EFA) for ESEM
Usage
esem_efa(
data,
nfactors,
fm = "ML",
rotate = "geominT",
scores = "regression",
residuals = TRUE,
Target = NULL,
missing = TRUE
)
Arguments
data |
is a raw data matrix. |
nfactors |
is number of factors to extract |
fm |
is the factoring method. |
rotate |
is the rotation method to be used. The suggested methods are available in psych::fa() |
scores |
is the factor scores to be used in EFA estimation. The default scores are estimated using regression as set in "regression". |
residuals |
is set to FALSE by default. In case the residual matrix is required in the output, this parameter should be set to TRUE |
Target |
is the target rotation matrix to be used. In case no target matrix is provided, EFA proceeds with alternative approach. The list of target rotations are available from GPArotation |
missing |
is used with scores set to TRUE. The default is missing=TRUE which imputes missing values using either the median or the mean. |
Value
Eigen values of the common factor solution and reporting results for EFA stage
Examples
sdq_lsac<-sdq_lsac
esem_efa(data=sdq_lsac,
nfactors=5,
fm = 'ML',
rotate="geominT",
scores="regression",
residuals=TRUE,
missing=TRUE)