Log-likelihood, number of observations, and information criteria

logLik() returns the log-likelihood of a fitted model with its number of free parameters (df) and observations (nobs), so that stats::AIC() and stats::BIC() work directly. For a measurement model this is the Step-1 log-likelihood. For structural models it is the log-likelihood of the joint model for the indicators and the structural variables evaluated with the Step-1 parameters held fixed; for a tseLCA_both object it is the distal-outcome component, which conditions on the covariates.

Usage

# S3 method for class 'tseLCA'
logLik(object, ...)

# S3 method for class 'tseLCA'
nobs(object, ...)

Arguments

object: A fitted tseLCA object.
...: Further arguments (currently unused).

Value

logLik(): an object of class "logLik". nobs(): an integer.

Examples

d   <- generate_data(200, "high", "covariate", seed = 1)
fit <- three_step(d, paste0("Y", 1:6), n_classes = 3,
                  Zp.names = "Zp", use.simple.cov = TRUE)
logLik(fit)
#> 'log Lik.' -548.6403 (df=22)
AIC(fit)
#> [1] 1141.281
BIC(fit)
#> [1] 1213.844
nobs(fit)
#> [1] 200