Fit Measures for a Latent Variable Model estimated using INLA

Fit Measures for a Latent Variable Model estimated using INLA

Arguments

object

An object of class INLAvaan.

fit.measures

If "all", all fit measures available will be returned. If only a single or a few fit measures are specified by name, only those are computed and returned. The LOO measures "elpd_loo", "se_loo", "p_loo" and "looic" (see loo()) are included in "all" only when a LOO result is stored with the fit (test = "loo" in inlavaan() or add_loo()); otherwise they are computed on demand when requested by name, and recomputed on every call – store the result with fit <- add_loo(fit) (or call loo() directly) for repeated access.

baseline.model

An optional INLAvaan object representing the baseline (null) model. Required for incremental fit indices (BCFI, BTLI, BNFI). Must have been fitted with test != "none".

h1.model

Ignored (included for compatibility with the lavaan generic).

fm.args

Ignored (included for compatibility with the lavaan generic).

output

Ignored (included for compatibility with the lavaan generic).

...

Additional arguments. Currently supports:

rescale

Character string controlling how the Bayesian chi-square is computed, following blavaan::blavFitIndices(). Options are "devM" (default) which uses the deviance rescaled by pD from DIC, or "MCMC" which uses the classical chi-square ((N-1) * F_ML) and classical degrees of freedom (p - npar) at each posterior sample.

Value

A named numeric vector of fit measures.

See also

bfit_indices(), compare(), diagnostics()

Examples

# \donttest{
HS.model <- "
  visual  =~ x1 + x2 + x3
  textual =~ x4 + x5 + x6
  speed   =~ x7 + x8 + x9
"
utils::data("HolzingerSwineford1939", package = "lavaan")
fit <- acfa(HS.model, HolzingerSwineford1939, std.lv = TRUE, nsamp = 100,
            verbose = FALSE)

# All available fit measures
fitMeasures(fit)
#>         npar   margloglik          ppp          dic        p_dic       BRMSEA 
#>           21    -3848.435        0.000     7552.455       20.654        0.115 
#>    BGammaHat adjBGammaHat          BMc     elpd_loo        p_loo        looic 
#>        0.933        0.877        0.851    -3769.452       24.047     7538.905 
#>       se_loo    elpd_waic       p_waic         waic      se_waic 
#>       85.970    -3768.864       22.839     7537.728       85.792 

# Specific measures
fitMeasures(fit, c("npar", "DIC", "pD", "ppp"))
#>  npar   ppp 
#>    21 0.000 
# }