Calculate factor scores or factor-score coefficients for the latent variables in a structural-equation model.
# S3 method for sem
fscores(model, data=model$data, center=TRUE, scale=FALSE, ...)
# S3 method for msem
fscores(model, data=model$data, center=TRUE, scale=FALSE, ...)Either a matrix of estimated factor scores (if the data argument is
supplied) or a matrix of factor-score coefficients (otherwise). In the case of an "msem"
argument, a list of matrices is returned.
an object of class "sem" or "msem", produced by the sem
function.
an optional numeric data frame or matrix containing the observed variables
in the model; if not NULL, the estimated factor scores are returned; if NULL, the
factor-score coefficients are returned. The default is the data element of model,
which is non-NULL if the model was fit to a data set rather than a covariance or moment matrix.
if TRUE, the default, the means of the observed variables are
subtracted prior to computing factor scores. One would normally use this option
if the model is estimated from a covariance or correlation matrix among the
observed variables.
if TRUE, the possibly centered variables are divided by their
root-mean-squares; the default is FALSE.
One would normally use this option if the model is estimated
from a correlation matrix among the observed variables. Centering and scaling
are performed by the scale function.
arguments to pass down.
John Fox jfox@mcmaster.ca
Factor-score coefficients are computed by the “regression” method as \(B = C^{-1} C^{*}\), where \(C\) is the model-implied covariance or moment matrix among the observed variables and \(C^{*}\) is the matrix of model-implied covariances or moments between the observed and latent variables.
Bollen, K. A. (1989) Structural Equations With Latent Variables. Wiley.
sem, scale