Compute model predicted residuals for each variable using regression estimated factor scores.
obs.resid(data, model, ...)# S3 method for obs.resid
print(x, restype = "obs", ...)
# S3 method for obs.resid
plot(
x,
y = NULL,
main = "Observed Residuals",
type = c("p", "h"),
restype = "obs",
...
)
matrix or data.frame
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
an object of class obs.resid
type of residual used, either 'obs' for observation value
(inner product), 'res' or 'std_res' for unstandardized and standardized
for each variable, respectively
a NULL value ignored by the plotting function
the main title of the plot
type of plot to use, default displays points and lines
Phil Chalmers rphilip.chalmers@gmail.com
Chalmers, R. P. & Flora, D. B. (2015). faoutlier: An R Package for Detecting Influential Cases in Exploratory and Confirmatory Factor Analysis. Applied Psychological Measurement, 39, 573-574. tools:::Rd_expr_doi("10.1177/0146621615597894")
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. tools:::Rd_expr_doi("10.3389/fpsyg.2012.00055")
gCD, LD, robustMD