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)