model_parameters.befa: Parameters from Bayesian Exploratory Factor Analysis

In parameters: Processing of Model Parameters

Parameters from Bayesian Exploratory Factor Analysis

Description

Format Bayesian Exploratory Factor Analysis objects from the BayesFM package.

Usage

## S3 method for class 'befa'
model_parameters(
  model,
  sort = FALSE,
  centrality = "median",
  dispersion = FALSE,
  ci = 0.95,
  ci_method = "eti",
  test = NULL,
  verbose = TRUE,
  ...
)

Arguments

model	Bayesian EFA created by the BayesFM::befa.
sort	Sort the loadings.
centrality	The point-estimates (centrality indices) to compute. Character (vector) or list with one or more of these options: "median", "mean", "MAP" (see map_estimate()), "trimmed" (which is just mean(x, trim = threshold)), "mode" or "all".
dispersion	Logical, if TRUE, computes indices of dispersion related to the estimate(s) (SD and MAD for mean and median, respectively). Dispersion is not available for "MAP" or "mode" centrality indices.
ci	Value or vector of probability of the CI (between 0 and 1) to be estimated. Default to 0.95 (⁠95%⁠).
ci_method	The type of index used for Credible Interval. Can be "ETI" (default, see eti()), "HDI" (see hdi()), "BCI" (see bci()), "SPI" (see spi()), or "SI" (see si()).
test	The indices of effect existence to compute. Character (vector) or list with one or more of these options: "p_direction" (or "pd"), "rope", "p_map", "equivalence_test" (or "equitest"), "bayesfactor" (or "bf") or "all" to compute all tests. For each "test", the corresponding bayestestR function is called (e.g. rope() or p_direction()) and its results included in the summary output.
verbose	Toggle warnings.
...	Arguments passed to or from other methods.

Value

A data frame of loadings.

Examples

library(parameters)

if (require("BayesFM")) {
  efa <- BayesFM::befa(mtcars, iter = 1000)
  results <- model_parameters(efa, sort = TRUE, verbose = FALSE)
  results
  efa_to_cfa(results, verbose = FALSE)
}

parameters documentation built on Nov. 2, 2023, 6:13 p.m.