objectiveML, objectiveGLS, objectiveFIML, msemObjectiveML,
and msemObjectiveGLS Objective FunctionsThese functions are for objects fit by sem using the objectiveML (multivariate-normal full-information maximum-likelihood), link{objectiveFIML} (multivariate-normal full-information maximum-likihood in
the presence of missing data),
objectiveGLS (generalized least squares), and msemObjectiveML (multigroup multivariate-normal FIML) objective functions.
# S3 method for objectiveML
anova(object, model.2, robust=FALSE, ...)
# S3 method for objectiveFIML
anova(object, model.2, ...)# S3 method for objectiveML
logLik(object, ...)
# S3 method for objectiveFIML
logLik(object, saturated=FALSE,
intercept="Intercept", iterlim=1000, ...)
# S3 method for objectiveML
deviance(object, ...)
# S3 method for objectiveFIML
deviance(object, saturated.logLik, ...)
# S3 method for msemObjectiveML
deviance(object, ...)
# S3 method for objectiveML
AIC(object, ..., k)
# S3 method for objectiveFIML
AIC(object, saturated.logLik, ..., k)
# S3 method for msemObjectiveML
AIC(object, ..., k)
# S3 method for objectiveML
AICc(object, ...)
# S3 method for objectiveFIML
AICc(object, saturated.logLik, ...)
# S3 method for msemObjectiveML
AICc(object, ...)
# S3 method for objectiveML
BIC(object, ...)
# S3 method for objectiveFIML
BIC(object, saturated.logLik, ...)
# S3 method for msemObjectiveML
BIC(object, ...)
# S3 method for objectiveML
CAIC(object, ...)
# S3 method for objectiveFIML
CAIC(object, saturated.logLik, ...)
# S3 method for objectiveML
print(x, ...)
# S3 method for objectiveGLS
print(x, ...)
# S3 method for objectiveFIML
print(x, saturated=FALSE, ...)
# S3 method for msemObjectiveML
print(x, ...)
# S3 method for msemObjectiveGLS
print(x, ...)
# S3 method for objectiveML
summary(object, digits=getOption("digits"),
conf.level=.90, robust=FALSE, analytic.se=object$t
an object inheriting from class objectiveML, objectiveGLS,
objectiveFIML, msemObjectiveML, or msemObjectiveGLS.
if TRUE, compute robust standard errors or test.
a character vector of ``fit indices'' to report; the allowable values are those given in Usage
above, and vary by the objective function. If the argument isn't given then the fit indices reported are taken
from the R fit.indices option; if this option isn't set, then only the AIC and BIC are reported for models fit
with objectiveML, objectiveFIML, or msemObjectiveML, and no fit indices are reported for
models fit with objectiveGLS or msemObjectiveGLS.
ignored.
digits to be printed.
level for confidence interval for the RMSEA index (default is .9).
use analytic (as opposed to numeric) coefficient standard errors; default is TRUE
where analytic standard errors are available if there are no more than
100 parameters in the model and FALSE otherwise.
if TRUE (the default is FALSE); compute the log-likelihood (and statistics that
depend on it) for the saturated model when the objective function is FIML in the presence of missing data.
This can be computationally costly.
the name of the intercept regressor in the raw data, to be used in calculating the
saturated log-likelihood for the FIML estimator; the default is "Intercept".
the log-likelihood for the saturated model, as returned by logLik
with saturated=TRUE; if absent, this will be computed and the computation can be time-consuming.
iteration limit used by the nlm optimizer to compute the saturated log-likelihood for
the FIML estimator with missing data; defaults to 1000.
John Fox jfox@mcmaster.ca and Jarrett Byrnes
See sem.
sem, objective.functions, modIndices.objectiveML