EFA: Exploratory factor analysis (EFA).

Description Usage Arguments Value Note See Also Examples

View source: R/bruceR_stats_02_scale.R

Description

An extension of jmv::efa().

Usage

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

Arguments

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.

Value

No return value.

Note

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

See Also

jmv::efa()

Examples

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

bruceR documentation built on June 22, 2021, 1:06 a.m.