sem (version 2.1-0)

ML.methods: Methods for sem Objects Fit Using the objectiveML and objectiveGLS Objective Functions

Description

These functions are for objects fit by sem using the objectiveML (multivariate-normal full-information maximum-likelihood) and objectiveGLS (generalized least squares) objective functions.

Usage

## S3 method for class 'objectiveML':
anova(object, model.2, robust=FALSE, ...)

## S3 method for class 'objectiveML':
logLik(object, ...)
## S3 method for class 'objectiveML':
deviance(object, ...)
## S3 method for class 'objectiveML':
AIC(object, ..., k)
## S3 method for class 'objectiveML':
AICc(object, ...)
## S3 method for class 'objectiveML':
BIC(object, ...)
## S3 method for class 'objectiveML':
CAIC(object, ...)

## S3 method for class 'objectiveML':
print(x, ...)
## S3 method for class 'objectiveGLS':
print(x, ...)
## S3 method for class 'objectiveML':
summary(object, digits=5, conf.level=.90, robust=FALSE, analytic.se=object$t 

Arguments

object, model.2, x

an object inheriting from class objectiveML or objectiveGLS.

robust

if TRUE, compute robust standard errors or test.

k, ...

ignored.

digits

digits to be printed.

conf.level

level for confidence interval for the RMSEA index (default is .9).

analytic.se

use analytic (as opposed to numeric) coefficient standard errors; default is TRUE is there are no more than 100 parameters in the model and FALSE otherwise.

References

See sem.

See Also

sem, objective.functions, modIndices.objectiveML