sem.fitres: Fitted values and residuals

In influence.SEM: Case Influence in Structural Equation Models

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 lavaan.

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)

influence.SEM documentation built on May 11, 2022, 9:05 a.m.