| sem.fitres {influence.SEM} | R Documentation |
Fitted values and residuals
Description
It calculates the expected values and the residuals of a sem model.
Usage
sem.fitres(object)
obs.fitres(object)
lat.fitres(object)
Arguments
object |
An object of class |
Details
The main function, sem.fitres(), calls one of the other two routines depending on the type of the model. If model does not contain latent variables, sem.fitres() calls the function obs.fitres(), otherwise calls the function lat.fitres().
The functions obs.fitres() and lat.fitres() are internal functions, do not use it directly.
Value
Returns a data frame containing:
1) The observed model variables; 2) The expected values on dependent variables (indicated with hat.); 3) The residuals on dependent variables (indicated with e.)
Note
In order to compute more interpretable fitted values and residuals, model is forced to have meanstrucure = TRUE and std.lv = TRUE.
Author(s)
Massimiliano Pastore
Examples
data("PDII")
model <- "
F1 =~ y1+y2+y3+y4
"
fit0 <- sem(model, data=PDII)
out <- sem.fitres(fit0)
head(out)
par(mfrow=c(2,2))
plot(e.y1~hat.y1,data=out)
plot(e.y2~hat.y2,data=out)
plot(e.y3~hat.y3,data=out)
plot(e.y4~hat.y4,data=out)
qqnorm(out$e.y1); qqline(out$e.y1)
qqnorm(out$e.y2); qqline(out$e.y2)
qqnorm(out$e.y3); qqline(out$e.y3)
qqnorm(out$e.y4); qqline(out$e.y4)