bruceR: EFA – R documentation

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EFA

Exploratory factor analysis (EFA).

An extension of jmv::efa().

EFA(
  data,
  vartext,
  method = "eigen",
  extraction = "pa",
  rotation = "varimax",
  nFactors = 1,
  hideLoadings = 0.3
)

`data`	Data frame.
`vartext`	Character string specifying the model (e.g., `"X[1:5] + Y[c(1,3)] + Z"`).
`method`	`"eigen"` (default), `"parallel"`, or `"fixed"`, the way to determine the number of factors.
`extraction`	`"pa"` (default), `"ml"`, or `"minres"`, using "principal axis", "maximum likelihood", or "minimum residual" as the factor extraction method, respectively.
`rotation`	`"varimax"` (default), `"oblimin"`, or `"none"`, the rotation method.
`nFactors`	An integer (default is 1) fixing the number of factors. Only relevant when `method="fixed"`.
`hideLoadings`	A number (0~1, default is 0.3) for hiding factor loadings below this value.

No return value.

It does not have the extraction method "Principal Components". You may still use SPSS.

EFA(bfi, "E[1:5] + A[1:5] + C[1:5] + N[1:5] + O[1:5]", method="fixed", nFactors=5)

Broadly Useful Convenient and Efficient R Functions

v0.6.2

GPL-3

Authors

Han-Wu-Shuang Bao [aut, cre]

Initial release

2021-04-08