Compute model predicted residuals for each variable using regression
estimated factor scores.
Usage
obs.resid(data, model, ...)
## S3 method for class 'obs.resid'
print(x, restype = "obs", ...)
## S3 method for class 'obs.resid'
plot(x, y = NULL, main = "Observed Residuals",
type = c("p", "h"), restype = "obs", ...)
Arguments
data
matrix or data.frame
model
if a single numeric number declares number of factors to extract in
exploratory factor analysis. If class(model) is a sem (semmod), or lavaan (character),
then a confirmatory approach is performed instead
...
additional parameters to be passed
x
an object of class obs.resid
restype
type of residual used, either 'obs' for observation value
(inner product), 'res' or 'std_res' for unstandardized and standardized
for each variable, respectively
y
a NULL value ignored by the plotting function
main
the main title of the plot
type
type of plot to use, default displays points and lines
Flora, D. B., LaBrish, C. & Chalmers, R. P. (2012). Old and new ideas for data screening and assumption testing for
exploratory and confirmatory factor analysis. Frontiers in Psychology, 3, 1-21.