fit_modsem_da: Fit measures for QML and LMS models

In modsem: Latent Interaction (and Moderation) Analysis in Structural Equation Models (SEM)

Fit measures for QML and LMS models

Description

Calculates chi-sq test and p-value, as well as RMSEA for the LMS and QML models. Note that the Chi-Square based fit measures should be calculated for the baseline model, i.e., the model without the interaction effect

Usage

fit_modsem_da(
  model,
  chisq = TRUE,
  lav.fit = FALSE,
  drop.list.single.group = TRUE
)

Arguments

model	fitted model. Thereafter, you can use 'compare_fit()' to assess the comparative fit of the models. If the interaction effect makes the model better, and e.g., the RMSEA is good for the baseline model, the interaction model likely has a good RMSEA as well.
chisq	should Chi-Square based fit-measures be calculated?
lav.fit	Should fit indices from the lavaan model used to optimize the starting parameters be included (if available)? This is usually only approprioate for linear models (i.e., no interaction effects), where the parameter estimates for LMS and QML are equivalent to ML estimates from lavaan.
drop.list.single.group	Logical. If FALSE, (some) results are returned as a list, where each element corresponds to a group (even if there is only a single group). If TRUE, the list will be unlisted if there is only a single group

modsem documentation built on Nov. 19, 2025, 1:07 a.m.