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Print and format a multigroup factor analysis

Source: R/print.efa_group.R
print.efa_group.Rd

print() turns an efa_group() result into a sectioned report: a header recapping the groups, the common number of factors, the estimator, the rotation, and the alignment; a group-pair table of the matched Tucker congruences between the aligned loadings; a per-pair summary of the cross-group loading differences (with the salient and, when a bootstrap was run, the confidence-interval flags); and, when invariance = TRUE, a group-pair by factor grid of the approximate-invariance verdicts. format() assembles the same report and returns it as a character vector; print() is cat(format(x), sep = "\n"). The lines follow the active console theme, so they are plain when colours are disabled (for example when captured into a file or stripped with cli::ansi_strip()). print() does not draw a plot; use plot.efa_group().

Usage

# S3 method for class 'efa_group'
print(x, digits = 3, ...)

# S3 method for class 'efa_group'
format(x, digits = 3, ...)

Arguments

x

An object of class efa_group (output from efa_group()).

digits

Integer. The number of decimal places the reported values are rounded to. Default is 3.

...

Not used; for consistency with the generic.

Value

print() returns its argument x invisibly. format() returns a character vector with the report lines (styled to the active console theme; plain when colours are disabled).

See also

Other factor analysis: efa_average(), efa_fit(), efa_group(), efa_mi(), plot.efa_group()

Examples

g <- rep(c("g1", "g2"), length.out = nrow(GRiPS_raw))
mg <- efa_group(GRiPS_raw, groups = g, n_factors = 1)
#> ℹ `x` is not a correlation matrix; computing correlations from the raw data.
#> ℹ `x` is not a correlation matrix; computing correlations from the raw data.
mg
#> ── Multigroup exploratory factor analysis ──────────────────────────────────────
#> 
#> 2 groups (g1, g2) · 1 factor · PAF extraction · unrotated
#> Aligned to a symmetric consensus target.
#> N: g1 = 405, g2 = 405
#> 
#> ── Factor congruence ───────────────────────────────────────────────────────────
#> 
#> Tucker's congruence between the aligned group loadings (matched factors):
#> 
#>            F1
#> g1 vs g2  .999
#> 
#> ── Loading differences ─────────────────────────────────────────────────────────
#> 
#> Absolute loading differences by group pair (salience threshold |Δ| ≥ .1):
#> 
#>           mean  median   min   max  rmse  flagged
#> g1 vs g2  .025    .017  .002  .075  .033      0/8

# format() returns the same lines as plain text:
writeLines(format(mg))
#> ── Multigroup exploratory factor analysis ──────────────────────────────────────
#> 
#> 2 groups (g1, g2) · 1 factor · PAF extraction · unrotated
#> Aligned to a symmetric consensus target.
#> N: g1 = 405, g2 = 405
#> 
#> ── Factor congruence ───────────────────────────────────────────────────────────
#> 
#> Tucker's congruence between the aligned group loadings (matched factors):
#> 
#>            F1
#> g1 vs g2  .999
#> 
#> ── Loading differences ─────────────────────────────────────────────────────────
#> 
#> Absolute loading differences by group pair (salience threshold |Δ| ≥ .1):
#> 
#>           mean  median   min   max  rmse  flagged
#> g1 vs g2  .025    .017  .002  .075  .033      0/8