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Prepare a survey instrument for exploratory factor analysis

Source: R/psychometrics.R
efa_report.Rd

Reports KMO sampling adequacy, Bartlett's test of sphericity, and a parallel analysis scree plot to inform factor number selection. The suggested number of factors from parallel analysis is returned in $suggested_nfactors. The report prepares the researcher to estimate an EFA solution with a separate package such as psych or lavaan.

Usage

efa_report(
  data,
  instrument,
  scales = NULL,
  nfactors = NULL,
  rotation = "oblimin"
)

Arguments

data

A tibble or data.frame of responses.

instrument

An sframe object.

scales

Character vector or NULL. Scale IDs whose items to include. When NULL, all scale items are pooled.

nfactors

Integer or NULL. Suggested number of factors to highlight on the scree plot. When NULL, the parallel analysis recommendation is used.

rotation

Character. The rotation method to display in the diagnostic notes. Does not affect the diagnostics themselves. Defaults to "oblimin".

Value

An object of class sframe_efa_report with elements kmo, bartlett, parallel, and suggested_nfactors.

See also

reliability_report(), cfa_syntax()

Examples

# \donttest{
if (requireNamespace("psych", quietly = TRUE)) {
  demo <- sframe_demo_data()
  er <- efa_report(demo$responses, demo$instrument)
  print(er)
}
#> EFA Readiness Diagnostics
#> 
#>   Items:          12
#>   Complete cases: 120
#>   KMO overall:    0.761
#>   Bartlett chi-sq: 665.84  df: 66  p: 0.0000
#>   Suggested factors (parallel analysis): 4
#>   Planned rotation: oblimin
#> 
#> Note: estimate the EFA solution with a dedicated modelling package.
# }