INLAvaan (version 0.2.4)

compare: Compare Bayesian Models Fitted with INLAvaan

Description

Compare two or more Bayesian SEM fitted with INLAvaan, reporting model-fit statistics and (optionally) fit indices side by side.

Usage

compare(x, y, ..., fit.measures = NULL)
# S4 method for INLAvaan
compare(x, y, ..., fit.measures = NULL)

Value

A data frame of class compare.inlavaan_internal containing model fit statistics, sorted by descending marginal log-likelihood.

Arguments

x

An INLAvaan (or inlavaan_internal) object used as the baseline (null) model. It is included in the comparison table and passed to fitMeasures() for incremental indices.

y, ...

One or more INLAvaan (or inlavaan_internal) objects to compare against the baseline.

fit.measures

Character vector of additional fit-measure names to include (e.g. "BRMSEA", "BCFI"). Use "all" to include every measure returned by fitMeasures(). The default (NULL) shows only the core comparison statistics.

Details

The first argument x serves as the baseline (null) model. All models (including the baseline) appear in the comparison table. The baseline is also passed to fitMeasures() when incremental fit indices (BCFI, BTLI, BNFI) are requested via fit.measures.

The default table always includes:

• npar: Number of free parameters.

• Marg.Loglik: Approximated marginal log-likelihood.

• logBF: Natural-log Bayes factor relative to the best model.

• DIC / pD: Deviance Information Criterion and effective number of parameters (when test != "none" was used during fitting).

Set fit.measures to a character vector of measure names (anything returned by fitMeasures()) to append extra columns. Use fit.measures = "all" to include every available measure.

References

https://lavaan.ugent.be/tutorial/groups.html

See Also

fitmeasures(), bfit_indices()

Examples

# \donttest{
# Model comparison on multigroup analysis (measurement invariance)
HS.model <- "
  visual  =~ x1 + x2 + x3
  textual =~ x4 + x5 + x6
  speed   =~ x7 + x8 + x9
"
utils::data("HolzingerSwineford1939", package = "lavaan")

# Configural invariance
fit1 <- acfa(HS.model, data = HolzingerSwineford1939, group = "school")

# Weak invariance
fit2 <- acfa(
  HS.model,
  data = HolzingerSwineford1939,
  group = "school",
  group.equal = "loadings"
)

# Strong invariance
fit3 <- acfa(
  HS.model,
  data = HolzingerSwineford1939,
  group = "school",
  group.equal = c("intercepts", "loadings")
)

# Compare models (fit1 = configural = baseline, always first argument)
compare(fit1, fit2, fit3)

# With extra fit measures
compare(fit1, fit2, fit.measures = c("BRMSEA", "BMc"))

# With incremental indices (baseline = fit1, passed to fitMeasures())
compare(fit1, fit2, fit3, fit.measures = c("BCFI", "BTLI"))
# }