difNLR (version 1.3.7)

logLik.ddfMLR: Loglikelihood and information criteria for an object of "ddfMLR" class.

Description

S3 methods for extracting loglikelihood, Akaike's information criterion (AIC) and Schwarz's Bayesian criterion (BIC) for an object of "ddfMLR" class.

Usage

# S3 method for ddfMLR
logLik(object, item = "all", ...)
# S3 method for ddfMLR
AIC(object, item = "all", ...)
# S3 method for ddfMLR
BIC(object, item = "all", ...)

Arguments

object

an object of "ddfMLR" class.

item

numeric or character: either character "all" to apply for all converged items (default), or a vector of item names (column names of Data), or item identifiers (integers specifying the column number).

...

other generic parameters for S3 methods.

See Also

ddfMLR for DDF detection among nominal data. logLik for generic function extracting loglikelihood. AIC for generic function calculating AIC and BIC.

Examples

# NOT RUN {
# Loading data based on GMAT
data(GMATtest, GMATkey)

Data <- GMATtest[, 1:20]
group <- GMATtest[, "group"]
key <- GMATkey

# Testing both DDF effects
(x <- ddfMLR(Data, group, focal.name = 1, key))

# AIC, BIC, log-likelihood
AIC(x)
BIC(x)
logLik(x)

# AIC, BIC, log-likelihood for the first item
AIC(x, item = 1)
BIC(x, item = 1)
logLik(x, item = 1)
# }