bifactorIndices_expl {BifactorIndicesCalculator}

bifactorIndices_expl

Description

Computes all available bifactor indices for the input given.

Usage

bifactorIndices_expl(Lambda, ItemsBySF = NULL, LoadMin = 0.2)

Arguments

Lambda

is a factor loading matrix from EFA or an object which can be converted to such. Currently only psych::fa() objects are supported.

ItemsBySF

is a list, indexed by factor, of vectors of item names belonging to each specific factor. You must NOT include the general factor in this list, and the list must have names which match the factor names in Lambda. It is recommended you look at the EFA solution first to see which factor is which. Defaults to NULL, in which case composition of specific factors is automated by comparing loadings to LoadMin

LoadMin

is the minimum loading size so that an item is considered to "belong" to a factor. If ItemsBySF is not provided, then items are assigned to factors based on whether their loading on that factor is greater than LoadMin. If ItemsBySF is provided, then warnings are issued whenever items load above LoadMin on factors to which they do not belong, or do not load above LoadMin on factors to which they do belong, LoadMin defaults to 0.2.

Details

Only standardized models are considered for exploratory models. PUC and ARPB are not supported for exploratory models currently, although that may change.

Value

A list of bifactor indices, including three different ECV indices, Omega, and OmegaH.

See Also

bifactorIndices, bifactorIndicesMplus, bifactorIndicesMplus_expl, bifactorIndicesMplus_ESEM, ECV_SS, ECV_SG, ECV_GS, IECV, Omega_S, Omega_H, H, FD

Examples

# psych::fa() can not access the rotations We have to load the library.
library(psych)
SRS_BEFA <- fa(SRS_data, nfactors = 5, rotate = "bifactor")

# inspect the solution to see which exploratory factors belong to which subdomain
SRS_BEFA$loadings
ItemsBySF = list(MR4 = paste0("SRS_", c(5, 9, 12, 15, 18)),
                MR2 = paste0("SRS_", c(1, 2, 8, 11, 17)),
                MR3 = paste0("SRS_", c(4, 6, 10, 14, 19)),
                MR5 = paste0("SRS_", c(3, 7, 13, 16, 20)))

bifactorIndices_expl(SRS_BEFA, ItemsBySF = ItemsBySF)