Usage
## S3 method for class 'objectiveML':
anova(object, model.2, robust=FALSE, ...)
## S3 method for class 'objectiveFIML':
anova(object, model.2, ...)
## S3 method for class 'objectiveML':
logLik(object, ...)
## S3 method for class 'objectiveFIML':
logLik(object, saturated=FALSE,
intercept="Intercept", iterlim=1000, ...)
## S3 method for class 'objectiveML':
deviance(object, ...)
## S3 method for class 'objectiveFIML':
deviance(object, saturated.logLik, ...)
## S3 method for class 'msemObjectiveML':
deviance(object, ...)
## S3 method for class 'objectiveML':
AIC(object, ..., k)
## S3 method for class 'objectiveFIML':
AIC(object, saturated.logLik, ..., k)
## S3 method for class 'msemObjectiveML':
AIC(object, ..., k)
## S3 method for class 'objectiveML':
AICc(object, ...)
## S3 method for class 'objectiveFIML':
AICc(object, saturated.logLik, ...)
## S3 method for class 'msemObjectiveML':
AICc(object, ...)
## S3 method for class 'objectiveML':
BIC(object, ...)
## S3 method for class 'objectiveFIML':
BIC(object, saturated.logLik, ...)
## S3 method for class 'msemObjectiveML':
BIC(object, ...)
## S3 method for class 'objectiveML':
CAIC(object, ...)
## S3 method for class 'objectiveFIML':
CAIC(object, saturated.logLik, ...)
## S3 method for class 'objectiveML':
print(x, ...)
## S3 method for class 'objectiveGLS':
print(x, ...)
## S3 method for class 'objectiveFIML':
print(x, saturated=FALSE, ...)
## S3 method for class 'msemObjectiveML':
print(x, ...)
## S3 method for class 'msemObjectiveGLS':
print(x, ...)
## S3 method for class 'objectiveML':
summary(object, digits=getOption("digits"),
conf.level=.90, robust=FALSE, analytic.se=object$t Arguments
object, model.2, x
an object inheriting from class objectiveML, objectiveGLS,
objectiveFIML, msemObjectiveML, or msemObjectiveGLS.
robust
if TRUE, compute robust standard errors or test.
fit.indices
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
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
where analytic standard errors are available if there are no more than
100 parameters in the model and FALSE otherwise.
saturated
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 cos
intercept
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".
saturated.logLik
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.
iterlim
iteration limit used by the nlm optimizer to compute the saturated log-likelihood for
the FIML estimator with missing data; defaults to 1000.