The hardware and bandwidth for this mirror is donated by dogado GmbH, the Webhosting and Full Service-Cloud Provider. Check out our Wordpress Tutorial.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]dogado.de.

Confirmatory Factor Analysis Workflow

Confirmatory Factor Analysis Workflow

This vignette outlines a small CFA workflow using the bundled continuous dataset.

library(PsychoMatic)
data(psychomatic_continuous)

Specify A Model

model <- "
factor1 =~ item1 + item2 + item3
factor2 =~ item4 + item5 + item6
"

Compare Candidate Models

compare_models_auto() uses lavaan directly and returns a compact table for alternative CFA specifications. ML-type estimators report information criteria when available, whereas WLSMV-style workflows compare models through scaled or robust fit indices when available. The code is not evaluated during vignette checks to keep package installation fast on constrained machines.

models <- list(
  one_factor = "general =~ item1 + item2 + item3 + item4 + item5 + item6",
  two_factor = model
)
comparison <- compare_models_auto(
  psychomatic_continuous,
  models = models,
  estimator = "ML",
  language = "eng"
)
comparison$fit

Full Automated CFA

The higher-level cfa_auto() function adds estimator selection, reliability, fit interpretation, warnings, and reporting tables. It is shown but not run by default in this vignette because it requires optional diagnostic packages.

cfa_result <- cfa_auto(
  psychomatic_continuous,
  model = model,
  estimator = "ML",
  language = "eng"
)
summary(cfa_result)

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
Health stats visible at Monitor.